We are looking for a Staff Forward Deployed Engineer who is passionate about solving complex cloud infrastructure challenges in the fast-growing AI/ML space. This is a high-impact position designed to be the "technical tip of the spear" for our most strategic AI-Native (ANE) customers.

As an FDE, you will sit at the intersection of Product Engineering and Customer Implementation. You will be embedded directly with our most strategic customers to drive transformational AI adoption. You will collaborate closely with customer teams to ship advanced AI applications that solve real world business problems.

You will build the tools, migration scripts, and AI starter kits that don't just solve one customer's problem, but scale the entire DigitalOcean AI Cloud ecosystem. Your mission is to accelerate "time-to-inference" in production at scale and serve as a critical feedback loop, ensuring our product roadmap is informed by the world's most demanding AI workloads.

What you’ll do:

• Embedded Customer Engineering: Partner deeply with strategic ANEs to manage complex migrations, build production-ready PoCs, and execute hands-on application builds on our GPU infrastructure.
• Build Scalable Assets & Tooling: Operationalize field learning by building migration planners, reusable systems, benchmarking frameworks, model optimization agents, and deployment automation scripts (e.g., Terraform/Pulumi) that standardize how AI workloads are deployed and tuned across DigitalOcean.
• Develop AI "Starter Kits": Create pre-built GenAI agents, solution templates, and notebooks (e.g., LangGraph, CrewAI) tailored to popular and advanced business needs.
• Drive the Product Roadmap: Act as the frontline technical voice for CPTO, surfacing architectural gaps and edge cases to inform core product development. Transition field-built tools into native product features.
• New Tech Validation: Lead the early testing and integration of emerging AI frameworks to ensure a first-class developer experience on DigitalOcean.
• Partner & GTM Enablement: Co-develop delivery frameworks with Strategic and Technical partners to enable repeatable, high-quality deployments at scale.
• Market Leadership: Produce field-tested demo kits and deployment guides that support new product releases with practical, validated assets.

Key Metrics

• Customer Adoption: Number of high-impact production workloads landed; reduction in average "time-to-production"; and Pilot-to-Production conversion rates.
• Asset & Tooling Delivery: Number of reusable tools (agents, scripts, playbooks) delivered per quarter and their subsequent adoption rate by the crossfunctional teams and customers.
• Field Enablement & Scale: Measured by the successful handoff and execution of FDE-defined deployment patterns to technical partners and the internal adoption rate of FDE playbooks across all customer-facing technical teams.
• Product Influence: Number of roadmap features or architectural changes directly attributed to FDE feedback and validated customer hypotheses.

What You’ll Add to DigitalOcean:

• AI/ML Architecture & Domain Expertise: Significant experience in the AI/ML lifecycle, specifically hosting large language or multimodal models using inference engines like vLLM, SGLang, or Modular. You have a deep understanding of common LLM architectures and optimization techniques (e.g., continuous batching, quantization).
• Distributed Systems & Infrastructure Mastery: Act as the subject matter expert on modern GPU families (NVIDIA/AMD) and their software stacks (CUDA, ROCm, TensorRT, OpenAI Triton). Expert proficiency in Kubernetes (K8s) and the design of distributed systems, including microservices, messaging systems, databases, and Infrastructure as Code. You can seamlessly integrate AI workloads with core cloud services (Networking, VPC, Storage, Compute).
• High-Performance Inference & Hardware Optimization: Hands-on experience with distributed inference serving frameworks (e.g., llm-d, NVIDIA Dynamo, or Ray Serve). You understand GPU-level optimization and have experience with interconnect technologies like NVlink, XGMI, or RoCE to maximize hardware efficiency.
• Software Engineering Foundation: Strong production coding skills in Python or Go with the ability to build high-quality tools, automation, and internal assets.
• Data-Driven Performance Insight: Proven ability to benchmark AI infrastructure and perform GPU utilization tuning to optimize customer ROI and workload performance.
• Consultative Execution: Proven ability to establish instant technical credibility with CTOs and Lead Architects while managing high-stakes technical migrations.

Preferred

• Experience with emerging AI orchestration frameworks like LangGraph, CrewAI, or LlamaIndex.
• A background in technical consulting or "Forward Deployed" roles at high-growth AI or infrastructure companies.
• Experience building and scaling "Center of Excellence" models or partner delivery frameworks.
• Active contributor to open-source AI projects or technical communities.

Compensation Range: 

• $195,000 - $239,000

*This is a remote role

JR: 2026-7748

#LI-Remote

Staff GenAI Research Scientist - Retrieval

P-1214

At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI platform, so our customers can focus on the high value challenges that are central to their own missions.

The Databricks AI Research organization enables companies to develop AI models and systems using their own data, with technologies ranging from pre-training LLMs from scratch to augmented generation using the latest retrieval techniques. Databricks AI does so by producing novel science and putting it into production. Databricks AI is committed to the belief that a company’s AI models are just as valuable as any other core IP, and that high-quality AI models should be available to all.

Job Description 

As a Staff Research Scientist on the Enterprise Agents team, you will be responsible for keeping up with the latest developments in Agent Context, Information Retrieval, Knowledge Assistants, RAG, Embeddings, and advancing the scientific frontier by creating new techniques that go beyond the state of the art. You will work together on a collaborative team of researchers and engineers with diverse backgrounds and technical training. And most importantly, you will love our customers: our goal is to make our customers successful in applying state-of-the-art LLMs and AI systems, and we encode our scientific expertise into our products to make that possible.

The Impact you will have

As a Staff Research Scientist on the AI Research Team at Databricks, You Will: 

• Define and lead independent research agendas on Information Retrieval for reusable Agent components, conducting experiments to empirically validate hypotheses and benchmark against state-of-the-art approaches.
• Drive research and technical strategy across enterprise retrieval and search, including workspace search, vector search.
• Drive algorithmic innovations for Retrieval within Large Language Models. 
• Experience with Agent Benchmarks for retrieval, text-embeddings and LLM Data Quality. 

What We Look for

• 5+ years of 
• PhD in Computer Science or related field with strong foundations in Natural Language Processing and Information Retrieval 
• Developing and implementing methods that extend and improve model capabilities, reliability, and safety. 
• Strong preference for candidates with first-author publications at top ML/systems conferences (EMNLP, ICLR, ACL, NeurIPs) focused on optimization or efficiency.

The Community You Will Join:

The Relevance & Personalization (R&P) team is Airbnb's matching intelligence engine — a talented team of ML engineers, applied researchers, and technical program managers who connect guests to the right listings across every surface and help hosts compete and thrive in our marketplace. We work at the intersection of search ranking, recommendations, personalization, and generative AI, and we're building toward a future where Airbnb feels less like a search engine and more like a knowledgeable travel companion that understands your needs across your entire trip journey.

The Difference You Will Make:

As Product Manager for Relevance & Personalization, you will help set the strategy and drive execution for some of Airbnb's highest-leverage AI systems. You'll own the roadmap and shape how personalization works across the guest journey, and help define how we close the feedback loop for hosts. You'll partner with engineers, researchers, designers, and cross-functional teams to ship systems that directly drive bookings, guest satisfaction, and host success — at global scale.

A Typical Day: 

• Define and drive the roadmap for Airbnb's relevance and personalization platform — from natural language query understanding to multi-turn, context-aware discovery experiences
• Make prioritization calls that balance multiple competing objectives: guest experience, host success, revenue, fairness, and marketplace health
• Partner with ML engineers and applied researchers to shape model strategy, evaluation frameworks, and experimentation design
• Align cross-functional partners — Guest, Host, MarTech, Trust & Safety, Customer Support — on shared goals and sequencing
• Drive the Tripcycle vision: ensuring R&P's intelligence layer connects across the full trip lifecycle, from inspiration through post-trip
• Design and oversee A/B experiments with rigorous metric design and long-term effect measurement
• Translate complex technical tradeoffs into clear decisions for engineering teams and concise narratives for leadership
• Foster an environment where engineers and product managers collaborate on building the future
• Stay close to guests and hosts: synthesize user research, marketplace data, and competitive signals to sharpen your intuition and refine strategy

Your Expertise:

• 10+ years of product management experience, with at least 3 years on ML, search, recommendations, or AI-powered products at scale
• Track record of owning strategy and roadmap for technically complex systems — not just managing features, but setting direction and making hard prioritization calls
• Strong experimentation fluency: comfortable designing A/B tests, interpreting counterfactual results, and reasoning about proxy metrics vs. long-term outcomes
• Experience working on two-sided marketplaces or platforms where you balanced supply-side and demand-side tradeoffs
• Ability to earn the respect of Staff and Principal-level engineers and researchers — you don't need to write code, but you need to engage at a level that builds credibility
• Clear, structured communicator who can distill complex technical tradeoffs for executives and translate strategic intent into actionable guidance for engineers
• Experience with LLM-based products in production — ideally involving evaluation challenges, latency constraints, or safety and guardrail work (preferred)
• Familiarity with reinforcement learning, contextual bandits, or explore/exploit frameworks in a product context (preferred)
• Background working alongside applied researchers or with teams that publish externally (preferred)

Your Location:

Due to the nature of this position, the successful applicant will need to be based in San Francisco, CA to be able to conduct their work. Currently, employees can not be located in: Alaska, Indiana, Nebraska, North Dakota, Ohio, South Dakota, Wisconsin, Alabama, Mississippi, Oklahoma, Delaware And Rhode Island. This list is continuously being updated, please check back with us if the state you live in is on the exclusion list.  If your position is employed by another Airbnb entity, your recruiter will inform you what states you are eligible to work from. 

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: reasonableaccommodations@airbnb.com. Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process. 

We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application.

About Loop

Loop is the data platform for the global supply chain. Logistics runs on messy, unstructured data—trapped in PDFs, emails, and legacy systems. We use AI to structure this chaos, creating a "source of truth" that automates payments and audits for the Fortune 100.

We are building the financial nervous system for a $100 trillion physical economy. Our technology ensures freight moves efficiently and carriers get paid instantly.

Backed by Founders Fund, Index Ventures and 8VC, we are scaling rapidly. We are looking for engineers ready to deploy production AI that powers the physical economy.

About the New Grad Program

Most AI stays in the browser. Ours moves atoms. You aren't just building features; you are building the autonomous brain for the Fortune 100’s global supply chain.

This program is designed to compress 3 years of learning into 1 year by throwing you into the deep end of production AI systems on Day 1. Instead of sandboxed projects, you get to solve real problems and impact customers directly. This program demands intense investment, but by the end, you will perform as a strong entry-level engineer jumpstarting your career.

The Schedule:

• Week 1 (Onboarding): Deep dive into tools and domain. You will ship code to production on Day 1 and fully grasp our dev loop by Friday.
• Months 1-3 (Velocity): You will deliver 3 entry-level projects with increasing ambiguity. By the end of Month 3, you are expected to operate as a fully independent engineer.
• Months 4-9 (The Rotation): You will rotate onto a different high-impact team to expand your surface area. Tracks include:
• Platform: AI infrastructure and Engineering Systems.
• Core Product: Audit, Billing, and Payments logic.
• Commercial: Revenue Activation and Forward Deployed Engineering.
• Special Projects: Partnering directly with the CEO/CTO and other execs
• Month 9+ (Graduation): You should demonstrate Mid-Level Engineer performance and will be considered for immediate promotion.

About You

We're not just looking for strong academic performers. We're looking for people who are genuinely driven to build things and go deep on hard problems. If the following resonates, you belong here:

• You go above and beyond. You have a repo, a side hustle, or a project you built just because you are curious. You’re self-directed and don't need an assignment to start coding.
• You have a bias towards action. You prefer to ship, break, fix, and apologize rather than wait for a committee decision.
• You are drawn to hard problems. You want problems that are more than one prompt away from a solution.
• You get absorbed in mastering your craft. Whether it’s climbing the Esports ladder, acing a math competition, winning a hackathon, or debugging a complex issue, you know what it feels like to lose track of time working on something you care about.

Responsibilities

• Ship critical infrastructure. Manage real-world logistics and financial data for the largest enterprise in the world.. 
• Own the why. Build deep context through customer calls, and understand the Loop’s value to our customers. You push back on requirements if you see a better, faster way to solve the customer’s problem.
• Full-stack proficiency. Work across system boundaries, from frontend UX to LLM agents, database schema and event infrastructures.
• Leverage AI tools to handle the 90% boilerplate, so you can focus the highest leverage 10%: quality, architecture, product taste.
• Raise the velocity bar. You will constantly optimize our dev loops, refactor legacy patterns, automate your own workflows and fix broken processes.

Qualifications

• Graduating with a BS or higher in STEM fields; available to start full-time in 2026.
• Working in person in the SF or Chicago office 4 days a week.
• Proficiency with modern techstack. You can deliver a modern web app in hours not in days..
• Unblocking yourself. You thrive in ambiguity. Despite the chaos, you deliver high quality products and business impact.
• AI Literate. You have strong intuition on how LLM works: where they excel and where they generate slop. You live and breathe AI native tools (Cursor, Codex, Claude Code etc.)

Compensation

• $150,000 annual base pay for SF
• $125,000 annual base pay for Chicago

Benefits & Perks

• Fully paid health insurance.
• 401k with matching.
• Unlimited PTO.
• Generous professional development budget.
• Commuter benefits.
• Wellness benefits
• Phone plan stipend

#LI-LOOP

Together AI is building the AI Inference & Model Shaping Platform that brings the most advanced generative AI models to the world. Our platform powers multi-tenant server-less workloads and dedicated endpoints, enabling developers, enterprises, and researchers to harness the latest LLMs, multimodal models, image, audio, video, and reasoning models at scale.

We are looking for an exceptional Engineering Lead to partner closely with our cross-functional engineering, infrastructure, research, and sales teams to ensure excellence of our ML API offerings. Your primary focus will be on delivering world-class inference and fine-tuning in our public APIs and customer deployments by building automation and operations processes.

This role is ideal for a highly motivated and technically adept individual who excels in fast-paced, dynamic environments. You will be in charge of designing and scaling our ML processes & tooling at production scale – optimizing operations to ensure availability and reliability for our services, across differing tenants and user loads, and in a multi-cluster deployment. You will serve as a passionate advocate for internal and external customers, providing feedback to the wider engineering and infrastructure teams to improve our systems and core business metrics. If you thrive in a collaborative, problem-solving environment and are driven to deliver operational excellence, we encourage you to apply for this exciting opportunity.

Key Responsibilities

• Own availability and performance SLAs for production inference and fine-tuning services across serverless and dedicated deployments
• Own & improve testing, deployment, configuration management, and monitoring practices for multi-cluster ML infrastructure – partnering closely with Infra SREs
• Build self-serve tooling and automation to reduce operational toil and enable self-serve offerings.
• Define and enforce configuration best practices for inference engines (SGLang, TRT-LLM, vLLM etc.) to prevent runtime issues
• Lead incident response, conduct postmortems, and drive reliability improvements
• Mentor team members and potentially grow into hiring/team building as the organization scales
• Partner with infrastructure and ML engineering teams to improve system reliability and cost efficiency

Required Qualifications

• 5+ years operating production ML inference or training systems at scale
• 2+ years in senior IC or tech lead roles, with demonstrated mentorship and technical leadership experience. Having built or scaled teams is a plus.
• Deep expertise with Kubernetes, multi-cluster orchestration, and ML serving frameworks
• Experience with multi-tenant SaaS platforms
• Proven track record of SLA ownership with specific metrics (99.9% uptime, p99 latency targets)
• Customer escalation and incident communication experience
• Experience with LLM inference serving systems (SGLang, vLLM, TRT-LLM, or similar)
• Ability to influence cross-functional teams and make deployment/architecture decisions

Nice to Have

• Experience building internal developer platforms or self-serve tooling
• Background in cost optimization for GPU infrastructure
• Contributions to open-source ML infrastructure projects

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $250,000 - $300,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

Together AI is building the AI Acceleration Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art AI cloud infrastructure.

As a Senior Backend Engineer, you will play a key role in building the next generation AI cloud platform – a highly available, global, blazing-fast cloud infrastructure that virtualizes cutting-edge ML hardware (GB200s/GB300s, BlueField DPUs) and enables state-of-the-art ML practitioners with self-serve AI cloud services, such as on-demand + managed Kubernetes and Slurm clusters. This platform serves both our internal StaaS products (inference, fine-tuning) and our external cloud customers, spanning dozens of data centers across the world.

Some of what you’ll work on:

• Work on a distributed GPU scheduling system for the on-demand clusters product, Instant Clusters.
• Build out a global management plane for managing our data center compute, networking, and storage.
• Design and build new customer-facing cloud platform services, delivering killer enterprise AI cloud features.

Responsibilities

• Identify, design, and develop foundational backend services that power Together’s cloud platform
• Analyze and improve the robustness and scalability of existing distributed systems, APIs, databases, and infrastructure
• Partner with product teams to understand functional requirements and deliver solutions that meet business needs
• Write clear, well-tested, and maintainable software and IaC for both new and existing systems
• Conduct design and code reviews, create developer documentation, and develop testing strategies for robustness and fault tolerance
• Participate in an on-call rotation to address critical incidents when necessary

Requirements

• 5+ years of demonstrated experience in building large scale, fault tolerant, distributed systems and API microservices
• Experience designing, analyzing and improving efficiency, scalability, and stability of various system resources
• Excellent communication skills – able to write clear design docs and work effectively with both technical and non-technical team members
• Demonstrated experience with building and operating high-performance and/or globally distributed microservice architectures across one or more cloud providers (AWS, Azure, GCP)
• Strong systems knowledge across compute, networking, and storage, including concurrency, memory management, performant I/O, and scale
• Experience developing against and managing a relational database, such as PostgreSQL
• Expert-level programmer in one or more of programming language (Golang preferred)
• Proficiency in version control practices and integrating IaC with CI/CD pipelines.
• Experience with Kubernetes and containers preferred
• Experience building and operating data infrastructure (Kinesis, Airflow, Kafka, etc) a plus
• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $160,000 - $230,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

As the Partnerships Manager for our Model Ecosystem, you will be the primary architect of Together AI’s model library. This is a high-impact, cross-functional role focused on bringing the world’s leading proprietary and open-source models onto the Together platform. You will navigate an ever-evolving landscape to negotiate non-standard, creative deals that provide developers with the best possible building blocks for AI applications.

You are a "deal-maker" who thrives in ambiguity. You will sit at the intersection of Product, Finance, and Marketing, ensuring that our model roadmap is not only technically superior but commercially viable and market-facing.

Responsibilities

• Negotiate & Manage Partnerships: Lead end-to-end deal cycles with model builders across all modalities (text, image, video, etc.). You will handle everything from initial outreach to negotiating complex, creative commercial terms for both proprietary and open-source models.
• Curate the Model Library: Act as the internal champion for our "Model Library," identifying which frontier and specialized models we should bring to Together AI to maintain our competitive edge.
• Product & Engineering Alignment: Work closely with the Product team to define "bring-up" requirements and ensure new models are integrated seamlessly into our inference and fine-tuning stacks.
• Commercial Strategy: Partner with Finance to construct deal structures that balance aggressive growth with sustainable unit economics, often involving non-standard incentive structures.
• Go-to-Market & Co-Selling: Collaborate with Partner Marketing to announce new integrations and create momentum. You will also engage in co-selling efforts, helping our Sales team understand how to leverage specific partner models to win enterprise deals.

Requirements

• Creative Deal Maker: You have a track record of constructing partnership agreements that don’t follow a standard template. You can navigate complex IP, revenue-share, and exclusivity discussions with ease.
• High EQ & Collaborative: You are partner-oriented. You know how to build trust quickly and find the "win-win" in a competitive environment.
• Technical Curiosity: While you don’t need to be an ML researcher, you should have the technical depth to discuss model architecture, context windows, and inference requirements with product teams.
• Relevant Experience: 5-7+ years in Business Development or Strategic Partnerships. We value experience from high-growth API, cloud infrastructure, or developer platform companies (think Stripe, MongoDB, or Twilio) where you managed complex ecosystems.
• AI-Native Mindset: You work at pace with a relentless sense of urgency. You prefer "done and iterating" over "perfect and stagnant."

Preferred Qualifications

• Direct experience working with LLM labs or open-source AI communities.
• Experience in "co-selling" motions where partnerships directly drove revenue.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $270K - 300K OTE + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy.  

About the Role

Together AI is seeking a Machine Learning Engineer to join our Inference Engine team, focusing on optimizing and enhancing the performance of our AI inference systems. This role involves working with state-of-the-art large language models models and ensuring they run efficiently and effectively at scale. If you are passionate about AI inference, PyTorch, and developing high-performance systems, we want to hear from you. This position offers the chance to collaborate closely with AI researchers and engineers to create cutting-edge AI solutions. Join us in shaping the future at Together AI!

Responsibilities

• Design and build the production systems that power the Together AI inference engine, enabling reliability and performance at scale.
• Develop and optimize runtime inference services for large-scale AI applications.
• Collaborate with researchers, engineers, product managers, and designers to bring new features and research capabilities to the world.
• Conduct design and code reviews to ensure high standards of quality.
• Create services, tools, and developer documentation to support the inference engine.
• Implement robust and fault-tolerant systems for data ingestion and processing.

Requirements

• 3+ years of experience writing high-performance, well-tested, production-quality code.
• Proficiency with Python and PyTorch.
• Demonstrated experience in building high performance libraries and tooling.
• Excellent understanding of low-level operating systems concepts including multi-threading, memory management, networking, storage, performance, and scale.
• Preferred: Knowledge of existing AI inference systems such as TGI, vLLM, TensorRT-LLM, Optimum
• Preferred: Knowledge of AI inference techniques such as speculative decoding.
• Preferred: Knowledge of CUDA/Triton programming.
• Nice to have: Knowledge of Rust, Cython and compilers.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society. Together, we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI. Our team has been behind technological advancements such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey to build the next-generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance, and other competitive benefits. The US base salary range for this full-time position is $160,000 - $230,000 + equity + benefits. Our salary ranges are determined by location, level, and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunities to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

About the role

As a Forward Deployed Engineer (FDE) focused on Inference & Post-Training, you will be a hands-on technical partner to our most strategic customers — production AI teams looking to leverage high quality models and do inference at scale. For us, FDE is not a replacement for a Solutions Architect; you will partner with our SAs as a deep-domain specialist in inference optimization, fine-tuning pipelines, and production deployment. As key contributors to both the CX, Engineering, and Sales organizations, FDEs add tremendous value by ensuring we can meet the requirements of our most complex POCs, facilitate successful platform adoption, and guide tailored optimization efforts — directly impacting customer success, company growth, and the hardening of our core platform.

Responsibilities

• Inference Engine Optimization: Select, configure, and optimize inference engine based on hardware, model architecture, and workload profile
• Configuration & Performance Tuning: Develop configuration updates to win critical POCs, benchmarks, and optimize customer deployments; tune KV cache, apply speculative decoding, determine optimal tensor parallelism, and determine quantization strategy to hit throughput and latency targets.
• Post-Training & Fine-Tuning: Drive hands-on RL training runs and optimize system design; guide customers through LoRA, SFT, DPO, RLHF, and GRPO pipelines from experimentation through production.
• Strategic Customer Alignment: Act as the primary technical point of contact for aligned strategic accounts — monitoring and optimizing endpoint configurations, helping customers get the most out of the platform, and collaborating to ensure we hit critical milestones.
• Opinionated Onboarding: Establish direct alignment with strategic customers at onboarding; ensure the right inference and post-training configurations are in place from day one to improve time-to-value.
• Product Feedback Loop: Directly influence our software and model roadmap by surfacing insights from the field. Contribute back to the product where needed to support customer requirements or drive a better experience. Drive early feature and research adoption with strategic logos.

Qualifications

• Experience: 5+ years in a technical role, with a strong focus on inference systems, open-source LLM deployment, or post-training workflows.
• Inference Engine Depth: Expert-level, hands-on experience with inference engines (e.g., vLLM, TensorRT-LLM, SGLang); ability to diagnose and resolve performance issues at the engine level.
• Inference Optimization: Deep knowledge of KV cache tuning, speculative decoding, tensor parallelism, pipeline parallelism, and quantization techniques
• Post-Training Knowledge: Hands-on experience with fine-tuning and post-training pipelines, including LoRA, SFT, DPO, RLHF, and GRPO; ability to advise on system design
• Model Landscape Awareness: Broad knowledge of state-of-the-art open-source models and strong judgment on model selection for specific customer use cases, hardware profiles, and performance targets.
• Coding Proficiency: Strong Python skills; comfortable working in production environments

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancements such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers on our journey in building the next generation of AI infrastructure. 

Compensation

We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $270,000 - $300,000 OTE + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. 

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our Privacy Policy at https://www.together.ai/privacy

About the Role

At Together.ai, we are building state-of-the-art infrastructure to enable efficient and scalable inference for large language models (LLMs). Our mission is to optimize inference frameworks, algorithms, and infrastructure, pushing the boundaries of performance, scalability, and cost-efficiency.

We are seeking an Inference Frameworks and Optimization Engineer to design, develop, and optimize distributed inference engines that support multimodal and language models at scale. This role will focus on low-latency, high-throughput inference, GPU/accelerator optimizations, and software-hardware co-design, ensuring efficient large-scale deployment of LLMs and vision models.

This role offers a unique opportunity to shape the future of LLM inference infrastructure, ensuring scalable, high-performance AI deployment across a diverse range of applications. If you're passionate about pushing the boundaries of AI inference, we’d love to hear from you!

Responsibilities

Inference Framework Development and Optimization

• Design and develop fault-tolerant, high-concurrency distributed inference engine for text, image, and multimodal generation models.
• Implement and optimize distributed inference strategies, including Mixture of Experts (MoE) parallelism, tensor parallelism, pipeline parallelism for high-performance serving.
• Apply CUDA graph optimizations, TensorRT/TRT-LLM graph optimizations, and PyTorch-based compilation (torch.compile), and speculative decoding to enhance efficiency and scalability.

Software-Hardware Co-Design and AI Infrastructure

• Collaborate with hardware teams on performance bottleneck analysis, co-optimize inference performance for GPUs, TPUs, or custom accelerators.
• Work closely with AI researchers and infrastructure engineers to develop efficient model execution plans and optimize E2E model serving pipelines.

Requirements

Must-Have:

• Experience:
  • 3+ years of experience in deep learning inference frameworks, distributed systems, or high-performance computing.
• Technical Skills:
  • Familiar with at least one LLM inference frameworks (e.g., TensorRT-LLM, vLLM, SGLang, TGI(Text Generation Inference)).
  • Background knowledge and experience in at least one of the following: GPU programming (CUDA/Triton/TensorRT), compiler, model quantization, and GPU cluster scheduling.
  • Deep understanding of KV cache systems like Mooncake, PagedAttention, or custom in-house variants.
• Programming:
  • Proficient in Python and C++/CUDA for high-performance deep learning inference.
• Optimization Techniques:
  • Deep understanding of Transformer architectures and LLM/VLM/Diffusion model optimization.
  • Knowledge of inference optimization, such as workload scheduling, CUDA graph, compiled, efficient kernels
• Soft Skills:
  • Strong analytical problem-solving skills with a performance-driven mindset.
  • Excellent collaboration and communication skills across teams.

Nice-to-Have:

• Experience in developing software systems for large-scale data center networks with RDMA/RoCE
• Familiar with distributed filesystem(e.g., 3FS, HDFS, Ceph)
• Familiar with open source distributed scheduling/orchestration frameworks, such as Kubernetes (K8S)
• Contributions to open-source deep learning inference projects.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $160,000 - $230,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

Together AI is building the best inference infrastructure for voice applications. Our Voice AI platform powers production-grade, real-time voice agents and applications — serving speech-to-text and text-to-speech models with best-in-class latency and reliability.

We're looking for a Senior ML Engineer to drive the model serving layer for voice workloads. You'll work hands-on with inference engines like TRT-LLM and SGLang to optimize how we serve models like Whisper, Parakeet, Orpheus, and Kokoro — pushing latency and throughput to the frontier. You'll profile GPU utilization, design batching strategies for streaming audio, and ensure new model architectures can go from research to production quickly.

This is a foundational hire on a small, high-impact team. Voice inference has unique challenges — streaming audio, tokenization, real-time latency budgets — that require dedicated ML engineering focus. You'll shape how Together serves voice models as the industry moves from pipeline architectures (ASR → LLM → TTS) toward end-to-end speech-to-speech.

• Own the model serving stack that powers Together's voice platform across STT, TTS, and speech-to-speech.
• Work directly with state-of-the-art accelerators (H100s, H200s, B200s) to optimize voice model inference.
• Collaborate with model partners (Cartesia, Deepgram, Rime, and others) to bring their models to production on Together's infrastructure.
• Build quality evaluation frameworks that guide model selection for customers and inform the roadmap.
• Join a small, early-stage team with outsized impact on a fast-growing product area.

Responsibilities

• Optimize inference performance for voice models (STT, TTS, speech-to-speech) — targeting best-in-class TTFB, throughput, and GPU utilization across our curated model set.
• Productionize voice models on serverless and dedicated endpoints, including batching strategies, streaming inference, and memory management tailored to audio workloads.
• Build and maintain a voice model evaluation framework — measuring WER across accents, languages, and noise conditions for STT; naturalness, latency, and pronunciation accuracy for TTS.
• Enable new model architectures in our serving stack as the field evolves, including audio-native LLMs, codec-based models (SNAC), and speech-to-speech systems.
• Collaborate with model partners to integrate and optimize their models (Cartesia, Deepgram, Rime, and others) running on Together's infrastructure.
• Profile and debug performance across the full inference stack — from GPU kernels to framework-level bottlenecks — and ship measurable improvements.
• Work with the platform engineering side of the team to ensure the serving layer meets the latency and reliability requirements of real-time voice APIs.
• Contribute to voice model fine-tuning capabilities (STT and TTS) as we enable customers to build differentiated voice experiences on Together.
• Lay the groundwork for multiple new products down the line.

Requirements

• 5+ years of experience in ML engineering, with a focus on model serving, inference optimization, or ML infrastructure.
• Hands-on experience with LLM serving engines (vLLM, SGLang, TensorRT-LLM, or similar) — comfortable reading and modifying engine internals, not just using APIs.
• Strong proficiency in Python and PyTorch; experience with GPU profiling and optimization (CUDA, memory management, kernel-level debugging).
• Track record of shipping ML systems to production with measurable performance improvements.
• Strong product sense — you think about what developers building voice apps actually need, not just what's technically interesting.
• Comfort working on a small, early-stage team where you'll wear multiple hats and move fast.
• Experience with speech and audio ML (ASR, TTS architectures, audio signal processing) is a strong plus but not required — you can learn this quickly if you have strong ML engineering fundamentals.
• Familiarity with audio codecs and tokenization schemes (SNAC, Encodec, DAC) is a plus.
• Experience training or fine-tuning speech models is a plus.
• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field, or equivalent practical experience

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $200,000 - $260,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

Together AI is building the AI Acceleration Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art AI cloud infrastructure.

As a Senior AI Infrastructure Engineer, you will play a key role in building the next generation AI cloud platform – a highly available, global, blazing-fast cloud infrastructure that virtualizes cutting-edge ML hardware (GB200s/GB300s, BlueField DPUs) and enables state-of-the-art ML practitioners with self-serve AI cloud services, such as on-demand + managed Kubernetes and Slurm clusters. This platform serves both our internal SaaS products (inference, fine-tuning) and our external cloud customers, spanning dozens of data centers across the world.

Responsibilities

• Design, build, and maintain performant, secure, and highly-available backend services/operators that run in our data centers and automate hardware management, such as Infiniband partitioning, in-DC parallel storage provisioning, and VM provisioning.
• Design and build out the IaaS software layer for a new GB200 data center with thousands of GPUs.
• Work on a global multi-exabyte high-performance object store, serving massive datasets for pretraining.
• Build advanced observability stacks for our customers with automated node lifecycle management for fault-tolerant distributed pretraining.
• Perform architecture and research work for decentralized AI workloads
• Work on the core, open-source Together AI platform
• Create services, tools, and developer documentation
• Create testing frameworks for robustness and fault-tolerance

To be successful, you’ll need to be deeply technical and possess excellent communication, collaboration, and diplomacy skills. You have strong fundamental software development skills. In addition, you have strong systems knowledge and troubleshooting abilities. 

Requirements

• 5+ years of professional software development experience and proficiency in at least one backend programming language (Golang desired)
• 5+ years experience writing high-performance, well-tested, production quality code
• Demonstrated experience with building and operating high-performance and/or globally distributed micro-service architectures across one or more cloud providers (AWS, Azure, GCP)
• Excellent communication skills – able to write clear design docs and work effectively with both technical and non-technical team members
• Deep experience with Kubernetes internals a big plus, such as implementing non-trivial Kubernetes operators, device/storage/network plugins, custom schedulers, or patches thereon or Kubernetes itself
• Deep experience with VMs/hypervisors a big plus, such as QEMU/KVM, cloud-hypervisor, VFIO, virtio, PCIE passthrough, Kubevirt, SR-IOV
• Deep experience with DC networking tech + solutions a big plus, such as VLAN, VXLAN, VPN, VPC, OVS/OVN
• Experience with Cluster API or similar a big plus
• Experience working on high-performance compute, networking, and/or storage a big plus
• Experience virtualizing GPUs and/or Infiniband a big plus
• Strong systems knowledge across compute, networking, and storage, including concurrency, memory management, performant I/O, and scale
• Experience with infrastructure automation tools (Terraform, Ansible), monitoring/observability stacks (Prometheus, Grafana), and CI/CD pipelines (GitHub Actions, ArgoCD)
• Experience building IaaS or PaaS systems at scale a plus
• Experience with DPUs/SmartNICs a plus
• GPU programming, NCCL, CUDA knowledge a plus 

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $160,000 - $230,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

You’ll join the Data Platform team, responsible for building the backend services and “data products” that power how data moves through the company. We create the core platform primitives - high-quality event streams, reliable access layers, and developer-friendly APIs/tools - so teams across the org can self-serve what they need and ship faster. You’ll design, build, and run backend services that create value from our company data, and make our data platform more self-serve (DIY)- so product and engineering teams can easily create and operate event-driven architectures, publish/consume streams, define access models, and ship data products end-to-end. You’ll also build LLM-adjacent services such as prompt categorization/taxonomy, enrichment, and metadata systems that turn raw telemetry into trusted, usable products.

Responsibilities

• Identify, design, and develop foundational data infrastructure components capable of handling millions or billions of events daily
• Analyze and improve the robustness and scalability of existing data processing infrastructure
• Partner with product teams to understand functional requirements and deliver solutions that meet business needs
• Write clear, well-tested, and maintainable infra-as-code and software for both new and existing systems
• Conduct design and code reviews, create developer documentation, and develop testing strategies for robustness and fault tolerance
• Participate in an on-call rotation to address critical incidents when necessary

Requirements

• 6+ years building production backend systems (distributed systems, APIs, data services).
• Strong skills in at least one backend language (e.g., Go, Python, Java, Rust) and API design (REST/gRPC).
• Demonstrated ability to own services end-to-end: design docs, implementation, testing, deployment, on-call, and iteration based on real usage.
• Strong engineering fundamentals: clean, maintainable code, thoughtful abstractions, strong design patterns, and systems that are easy to evolve.
• Solid data modeling and query skills (SQL) and experience with at least one of:

• • Streaming/eventing (Kafka/PubSub/Kinesis, etc.)
  • Workflow/compute (Airflow/Spark/Flink/Trino, etc.)
  • OLTP/OLAP stores and data lakes (Postgres + warehouse/lake tech)

• AI augmentation mindset:
  • You understand the state-of-the-art ways engineers use AI/LLMs to build software faster and better (e.g., coding copilots, agentic workflows, eval-driven iteration, retrieval/knowledge grounding), and you apply this thoughtfully to your own development and to the systems you build.
  • You have engineering judgment and you understand when AI Augmentation can fail or create team dynamics issues, putting mitigation mechanisms and guardrails in place.

Nice to have

• Experience building self-serve platforms (control planes, templates/golden paths, paved roads, multi-tenant services).
• LLM/AI product exposure: prompt/response telemetry, eval datasets, embeddings/RAG metadata, model/tool traces, privacy-safe logging.
• Security and governance experience: least-privilege access, auditability, data retention, PII handling.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $160,000 - $240,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

Together AI is looking for an ML Engineer who will develop systems and APIs that enable our customers to perform inference and fine tune LLMs. Relevant experience includes implementing runtime systems that perform inference at scale using AI/ML models from simple models up to the largest LLMs.

Requirements

• 5+ years experience writing high-performance, well-tested, production quality code
• Bachelor’s degree in computer science or equivalent industry experience
• Familiar with LLM inference ecosystem, including frameworks and engines (e.g. vLLM, SGLang, TRT, ...)
• Demonstrated experience in building large scale, fault tolerant, distributed systems like storage, search, and computation
• Expert level programmer in one or more of Python, Go, Rust, or C/C++
• Experience implementing runtime inference services at scale or similar

Responsibilities

• Design and build the production systems that power the Together Cloud inference and fine-tuning APIs, enabling reliability and performance at scale
• Partner with researchers, engineers, product managers, and designers to bring new features and research capabilities to the world
• Analyze and improve efficiency, scalability, and stability of various system resources
• Conduct design and code reviews
• Create services, tools & developer documentation
• Create testing frameworks for robustness and fault-tolerance
• Participate in an on-call rotation to respond to critical incidents as needed

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $160,000 - $220,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

The opportunity 

The Autonomous Freight Systems team is a brand new, AI-first engineering team in San Francisco. This team will own Flexport’s client-facing rates platform and the self-serve freight booking experience—two of the highest-leverage surfaces in our Client App that dictate how clients see pricing and book freight without manual intervention.

As a Staff Engineer, you will be the technical anchor for our next-generation AI-powered rates platform. We aren't just building a UI; we are building AI agents that handle real logistics work: parsing complex rate sheets, managing pricing intelligence across ocean, air, and trucking, and making "Self-Serve" a reality for thousands of shippers. You will build the intelligence layer that allows clients to commit freight on technology alone, with no account executive and no operations touch.

This is a ground-floor opportunity to shape technical direction, set up a new codebase, and build the platform that moves Flexport from an assisted-sales model to a tech-run one for the long tail of our client base. You will partner with Pricing, Sales, Ops, and Design on hard domain problems and ship to the most-used client surfaces at the company.

You will

• Design and ship end-to-end AI agents that handle pricing intelligence and booking compliance without human oversight.
• Create the tooling and secure AI infrastructure required to expose internal logistics data to LLMs safely.
• Navigate the rapidly evolving landscape of agent patterns, RAG, and prompt engineering to solve problems that don’t have "Stack Overflow" answers yet.
• Build and launch products rapidly and incrementally: we ship to production dozens of times per day.
• Mentor and uplevel engineers across the team, fostering a culture of technical excellence.
• Partner with the Engineering Manager to define the team’s technical roadmap and hiring bar.

You should have

• LLM Fluency: Experience with agent patterns, RAG, and prompt engineering. You know what works in production versus what only looks good in a demo.
• Agentic Orchestration: Experience with workflow orchestration (e.g., Temporal) and building reliable systems around non-deterministic AI.
• Entrepreneurial Drive: You don't wait for a spec; you find the highest-leverage automation problems and design the AI-driven solution.
• Product Instincts: You can identify what is worth building, not just execute on a spec. You have a proven track record of building data-heavy applications where high-quality user interaction is the priority.
• Architecture Leadership: Demonstrated experience leading technical initiatives across multiple teams or systems, specifically in building unified interfaces that aggregate data from various backend systems.
• Technical Rigor: A love of simple, well-tested code that is easy to extend and hard to break, combined with experience building large-scale distributed systems.
• Technical Communication: The ability to convey technical ideas in common terms to business partners, product managers, and engineers alike.

It's a plus if you have

• Experience with elements of our tech stack: Java, Spring Boot, Ruby on Rails, React, AWS.
• Experience in logistics, supply chain, or freight technology.
• Experience building internal tools or operator-facing applications.
• A bias for action: When you see a problem, you solve it.

#LI-onsite

What We're Looking For

As a Machine Learning Solutions Engineer, you will operate at the intersection of machine learning, distributed systems, and cloud infrastructure.
You will partner with customers to design and deploy end-to-end AI systems, spanning:

• Model development and training
• GPU infrastructure and cluster design
• Distributed inference and production deployment

This role goes beyond traditional ML solutions engineering—you will act as a technical architect, helping customers make critical decisions across compute, orchestration, and system design.

The role can be based out of our New York City or San Francisco office, with an in-office requirement of at least 2-3 days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this role at this time. The annual base pay range for this role is $150,000 - $195,000, in addition to a variable pay component and meaningful equity. 

What You’ll Do

Customer Architecture & Technical Leadership

• Partner with customers to understand ML workloads, infrastructure constraints, and scaling requirements
  
  
• Architect end-to-end solutions across:
  
  
• Data pipelines (CPU → GPU workflows)
  
  
• Distributed training (multi-node, multi-GPU)
  
  
• High-throughput inference systems
  
  
• Translate business goals (latency, cost, throughput) into technical system design decisions
  
  

GPU & Infrastructure Design

• Design and optimize workloads across GPU clusters (H100, H200, B200, etc.)
  
  
• Advise on:
  
  
• Training vs inference cluster design
  
  
• Interconnect choices (Ethernet vs Infiniband / RDMA vs Roce)
  
  
• Storage strategies (local NVMe vs networked / object storage)
  
  
• Model and optimize for:
  
  
• Tokens/sec, tokens/$
  
  
• Throughput vs latency tradeoffs
  
  
• GPU utilization and scheduling efficiency
  
  

Kubernetes & Platform Systems

• Design and support deployments on Kubernetes (EKS, GKE, on-prem clusters)
  
  
• Work with:
  
  
• GPU scheduling (time-slicing, MIG, bin-packing)
  
  
• Autoscaling and workload orchestration
  
  
• Helm-based deployments and multi-tenant environments
  
  
• Help customers balance:
  
  
• Raw Kubernetes flexibility vs platform abstraction (Lightning)
  
  

Demos, POCs, and Execution

• Build and deliver technical demos and POCs that showcase:
  
  
• Distributed training workflows
  
  
• Scalable inference endpoints
  
  
• End-to-end ML pipelines on Lightning AI
  
  
• Scope and lead POCs aligned to customer success metrics (latency, cost, reliability)
  
  

Cross-Functional Impact

• Act as the bridge between customers, product, and engineering
  
  
• Provide feedback on:
  
  
• Platform gaps in infrastructure, orchestration, and performance
  
  
• Emerging patterns in GPU usage and distributed systems
  
  
• Influence roadmap across ML workflows and infrastructure capabilities
  
  

Enablement & Thought Leadership

• Create technical content
• Architecture guides (e.g., high-throughput LLM inference systems)
• Best practices for GPU utilization and scaling
• Educate customers on modern AI infrastructure patterns

What You’ll Need

ML + Systems Expertise

• 3–6+ years experience in:
  
  
• Machine Learning / AI Engineering
  
  
• Solutions Engineering / Sales Engineering / ML Consulting
  
  
• Strong understanding of:
  
  
• Training vs inference workloads
  
  
• Model optimization (quantization, batching, caching, etc.)
  
  

GPU & Distributed Systems

• Experience working with:
  
  
• GPU clusters (NVIDIA stack preferred)
  
  
• Distributed training or inference systems
  
  
• Familiarity with:
  
  
• NCCL, CUDA, or GPU performance profiling
  
  
• Networking concepts (RDMA, Roce, Infiniband, high-throughput systems)
  
  

Kubernetes & Cloud Platforms

• Hands-on experience with:
  
  
• Kubernetes (EKS, GKE, or on-prem)
• Slurm 
• Containerization (Docker)
  
  
• Exposure to:
  
  
• GPU scheduling in Kubernetes environments
  
  
• Multi-tenant or production ML deployments
  
  

Programming & Tooling

• Strong Python skills (PyTorch preferred)
  
  
• Experience building:
  
  
• ML pipelines
  
  
• APIs or inference services
  
  
• Familiarity with Lightning AI, PyTorch Lightning, or similar frameworks is a plus
  
  

Customer-Facing Excellence

• • Ability to:
    
    
    • Explain complex infrastructure and ML tradeoffs clearly
      
      
    • Run technical discovery and uncover quantifiable success metrics
      
      
  • Experience working cross-functionally with:
    
    
    • Sales, product, and engineering teams

Want to help us help others? We’re hiring! 

GoFundMe is the world’s most powerful community for good, dedicated to helping people help each other. By uniting individuals and nonprofits in one place, GoFundMe makes it easy and safe for people to ask for help and support causes—for themselves and each other. Together, our community has raised more than $40 billion since 2010.

GoFundMe Pro  helps nonprofit organizations fundraise more effectively across donation experiences, peer-to-peer fundraising, and events. We’re looking for a Staff Product Manager to own high impact product areas across the supporter and nonprofit admin experience.

We’re looking for a Staff Product Manager to own high impact product areas across the donor experience. This role sits at the intersection of customer empathy, data, and emerging AI -building experiences that increase donor trust, conversion, and long-term engagement while delivering measurable business outcomes.

Candidates considered for this role will be located in the San Francisco Bay Area. There will be an in-office requirement of 3x a week

What You’ll Do

• Lead the end-to-end checkout experience, driving improvements in conversion, payment success rates, and donor retention
• Build delightful, intuitive experiences grounded in customer empathy and real-world behavior
• Leverage data, experimentation, and customer feedback to increase conversion.
• Operate with end-to-end accountability -from problem definition through delivery, optimization, and scale but in a way that you are leveraging the system and collaborating with others.
• Work cross-functionally with engineering, design, go-to-market, and data science partners to execute effectively
• Act as the voice of the customer, deeply understanding user needs, motivations, and pain points
• Use qualitative and quantitative insights to inform product and GTM decisions, define success metrics, and track outcomes
• Champion your product internally - building clarity, excitement, and alignment across teams while influencing without authority.
• Drive strong execution by transforming ambiguity into disciplined execution - defining scope, sequencing work, mitigating risks, coordinating stakeholders, and ensuring teams deliver against commitments.

You might thrive in this role if you:

• Bring 6+ years of product management experience, including leading growth initiatives for self-serve SaaS products
• Are skilled in Discovery that helps identify the right problems to solve and clearly articulate what not to build and why
• Are highly analytical and fluent in experimentation
• Operate effectively in fast-moving, ambiguous environments 
• Excel at aligning cross-functional teams and leading complex initiatives across product, engineering, and GTM teams
• Are AI Powered and actively use AI tools to accelerate work across the product development lifecycle - from discovery and synthesis to PRDs, experimentation, and iteration
• Leverage tools like Cursor and other AI-assisted workflows to improve speed, clarity, and decision quality in collaboration with Engineering and Design
• Are customer obsessed and growth minded

What You Bring

• 5+ years of product management experience with increasing scope, ownership, and measurable impact
• Proven track record of building, launching, and scaling successful products that drive customer and business outcomes. 
• Strong analytical and decision-making skills—comfortable using both data and judgment to drive outcomes
• Strong decision-making skills grounded in data, customer insight, and sound judgment
• Hands-on familiarity with AI tools (e.g., Cursor, LLM-based research, prototyping, or analytics tools) and comfort applying AI across the PDLC to improve speed and quality. 
• Experience working directly with customers and deeply analyzing consumer behavior and market trends
• Ability to operate independently, manage ambiguity, and perform at a fast pace under pressure
• Exceptional communication skills with the ability to align teams, present to senior leadership, and drive execution
• Humility, curiosity, and a bias toward learning

Nice to Have

• ​​MBA from a leading program, ideally focused on technology or entrepreneurship
• BA/BS in a technical field
• Background in management consulting
• Experience in fintech, payments, donations, or multi-stakeholder platforms

Why This Role Matters

You’ll shape products that don’t just grow revenue—but build trust, unlock value for customers, and create durable impact. This is a high-autonomy role for a product leader who thinks like a founder, ships with purpose, and is excited about what’s next.

Why you’ll love it here

• Make an Impact: Be part of a mission-driven organization making a positive difference in millions of lives every year.
• Innovative Environment: Work with a diverse, passionate, and talented team in a fast-paced, forward-thinking atmosphere.
• Collaborative Team: Join a fun and collaborative team that works hard and celebrates success together.
• Competitive Benefits: Enjoy competitive pay and comprehensive healthcare benefits.
• Holistic Support: Enjoy financial assistance for things like hybrid work, family planning, along with generous parental leave, flexible time-off policies, and mental health and wellness resources to support your overall well-being.
• Growth Opportunities: Participate in learning, development, and recognition programs to help you thrive and grow.
• Commitment to DEI: Contribute to diversity, equity, and inclusion through ongoing initiatives and employee resource groups.
• Community Engagement: Make a difference through our volunteering program.

We live by our core values: impatient to be great, find a way, earn trust every day, fueled by purpose. Be a part of something bigger with us!

GoFundMe is proud to be an equal opportunity employer that actively pursues candidates of diverse backgrounds and experiences.  We do not discriminate on the basis of race, color, religion, ethnicity, nationality or national origin, sex, sexual orientation, gender, gender identity or expression, pregnancy status, marital status, age, medical condition, mental or physical disability, or military or veteran status.

The total annual salary for this full-time position is $181,000- $240,000 + equity + benefits.  The company also offers equity and other benefits to employees, including healthcare, dental, vision, life insurance and 401(k) saving program. In addition to this wage, there are geolocation differentials that will increase pay depending on the work location. Additionally pay may vary depending on other factors including skills, experience, education, or training. Your recruiter can share more about the specific total compensation package based on your location during the hiring process.

If you require a reasonable accommodation to complete a job application or a job interview or to otherwise participate in the hiring process, please contact us at accommodationrequests@gofundme.com. 

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Depending on your location, the General Data Protection Regulation (GDPR) or certain US privacy laws may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available here. By submitting your application, you are agreeing to our use and processing of your data as required. 

Learn more about GoFundMe:

We’re proud to partner with GoFundMe.org, an independent public charity, to extend the reach and impact of our generous community, while helping drive critical social change. You can learn more about GoFundMe.org’s activities and impact in their FY ‘25 annual report.

Our annual “Year in Help” report reflects our community’s impact in advancing our mission of helping people help each other.

For recent company news and announcements, visit our Newsroom.

Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only

We use Metaview as part of our hiring process for jobs in NYC and certain features may qualify it as an automated employment decision tool (AEDT), as defined by New York City Local Law 144. As part of the hiring process, we provide Metaview with job requirements and candidate submitted resumes and application materials to assist in evaluating job-related qualifications. While this tool is used to improve efficiency and support our recruiting personnel, all final hiring decisions are made by GoFundMe employees.

We began using Metaview on March 10, 2026. The Metaview tool has been reviewed by an independent auditor. Results of the audit may be viewed here. The tool evaluates your professional experience, technical skills, education, and other qualifications using information collected directly from your submitted resume and application materials; all such data is retained in accordance with GoFundMe’s Personnel Privacy Notice and applicable legal requirements. If you would like to request an alternative selection process or a reasonable accommodation, please contact accommodationrequests@gofundme.com.

P-1549

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business.

The Mission

Databricks agents are only as good as the context they can retrieve. Whether an agent is answering a question about last quarter's revenue, debugging a failing job, generating SQL against a 10,000-table lakehouse, or summarizing a Wiki page, its quality is bounded by what it can find — and how well it understands what it finds.

We are hiring a Senior Staff Applied AI Engineer to own context retrieval for Databricks agents across SaaS providers. This is a zero-to-one role with two deeply connected charters:

1. Build the retrieval stack — query understanding, content understanding, ranking, retrieval, and evaluation — across the Enterprise SaaS data stored across multiple systems.
2. Build the search subagents that sit on top of that stack and reason about what context is needed, how to retrieve it, and whether the right thing actually came back — closing the loop between an agent's intent and the substrate that serves it.

If you have deep Information Retrieval wisdom, have shipped retrieval systems for RAG and agentic workloads, and want to build the substrate — and the agents on top of it — that make every Databricks agent measurably smarter, this role is for you.

What You Will Do

• Build the full retrieval stack from scratch. Own the end-to-end system: query understanding, content understanding and indexing, hybrid retrieval, ranking, and evaluation. Make the architectural calls that will define how Databricks agents access context for years to come.
• Retrieve across heterogeneous data — structured and unstructured. Index and rank across structured assets (tables, columns, SQL queries, dashboards, code, notebooks, jobs) and unstructured content (docs, wikis, tickets, chat, images, video, audio). Each modality has its own signals — design retrieval that exploits them rather than flattens them.
• Connect to the SaaS surface area customers actually use. Build connectors and retrieval adapters for the systems where enterprise knowledge lives. Treat each retrieval source with its own freshness, permissions, and ranking signals.
• Optimize for two consumers at once. Retrieval must serve both LLMs (grounded, token-efficient, hallucination-resistant context) and humans (intuitive, explainable discovery). These are different objectives and require different signals — own both.
• Crack query understanding for agents. Agent queries don't look like web queries. Build query rewriting, decomposition, intent classification, and entity resolution tuned for multi-turn agentic workflows.
• Crack content understanding at scale. Build the pipelines that extract structure, entities, embeddings, summaries, and metadata from every supported asset type — and keep them fresh as customer data evolves.
• Build search subagents that reason about retrieval. Design the agentic layer that decides what context is needed, which sources to query, how to decompose and route the search, and — critically — whether the retrieved content is actually sufficient to answer the question. These subagents will plan multi-hop searches, issue follow-up queries when results are weak, ground claims against retrieved evidence, and hand back high-confidence context (or signal failure) to upstream agents. This is where IR meets agentic reasoning.
• Build the evaluation flywheel for both retrieval and subagents. Stand up offline evals (nDCG, MRR, Recall@K, Precision@K), LLM-as-judge harnesses, human-in-the-loop labeling, and online experimentation. Extend evaluation beyond ranking metrics to measure subagent decision quality — did it ask the right follow-up?, did it correctly recognize when retrieval failed?, did it ground its answer in the right evidence?. Quality you can't measure is quality you can't ship.
• Set technical direction and grow the team. Set the multi-year roadmap, mentor senior engineers, partner with Research, Product, and Platform leaders, and raise the technical bar across the org.

What We're Looking For

• 10+ years of software engineering experience, with significant time spent building production retrieval, search, or RAG systems at scale.
• Deep Information Retrieval (IR) expertise: lexical retrieval (BM25, Lucene/Elasticsearch/OpenSearch), dense retrieval (embeddings, ANN indexes — FAISS, ScaNN, HNSW), hybrid retrieval, and learning-to-rank.
• Hands-on experience with modern LLM-era retrieval: RAG architectures, query rewriting, re-ranking with cross-encoders, long-context strategies, and grounding techniques that reduce hallucination.
• Experience designing agentic systems on top of retrieval — search planners, multi-hop / iterative retrieval, self-reflection and sufficiency checks, tool-using agents that decide what to fetch and verify what came back.
• Strong grasp of relevance evaluation: nDCG, MRR, Precision@K, Recall@K; offline/online experimentation; LLM-as-judge frameworks; building human labeling pipelines.
• Experience working across structured and unstructured data — you've indexed and ranked over tables, code, and documents in the same system, and have opinions about how to do it well.
• Track record of building 0→1: you've stood up a retrieval system from an empty repo, made the foundational architectural decisions, and grown it into something that customers depend on.
• Demonstrated ability to operate as a technical leader: setting direction across teams, mentoring senior engineers, and influencing roadmap with research, product, and platform partners.

Nice to Have

• Experience building retrieval over enterprise SaaS sources (permissions, freshness, multi-tenancy, ACL-aware indexing).
• Background in agentic systems, tool use, or multi-turn retrieval for LLM agents.
• Contributions to open-source IR/search projects, or publications at SIGIR, KDD, WWW, EMNLP, or similar venues.
• Experience training or fine-tuning embedding models, rerankers, or query understanding models.

Why This Role

• Foundational impact. Retrieval is the single biggest lever on agent quality. The stack you build will sit underneath every Databricks agent and every customer-built agent on our platform.
• Greenfield with scale. You get the rare combination of starting from a clean sheet and having immediate access to massive enterprise scale, real customer data, and a world-class research org.
• The right team. You'll work alongside engineers and researchers behind Lakehouse, Apache Spark™, Delta Lake, MLflow, MosaicML, and DBRX.

Location

This role is based in our Mountain View, CA or San Francisco, CA office. Hybrid in-office collaboration expected.

Airtable is the no-code app platform that empowers people closest to the work to accelerate their most critical business processes. More than 500,000 organizations—including 80% of the Fortune 100—rely on Airtable to transform how work gets done. 

Airtable has a design system with real foundations and a community of designers and engineers who contribute to it. We’re looking for someone who can be dedicated to building out and evolving this system, as well as bring a sharp point of view on how AI changes the way UI gets built. You’ll sit in Design, but your work lives equally in Figma and production code. This is a high-autonomy IC role with broad cross-functional reach.

What you'll do

• Collaborate on the existing system. Assess its state, establish direction with other contributors, and close the gap between design specs and implementation.
• Build and ship components and tokens yourself, while evolving contribution standards with the broader community of designers and engineers who maintain the system alongside you.
• Develop and evangelize a point of view on AI-assisted UI development. Experiment with tooling, workflows, and system structures that make AI a reliable collaborator for anyone writing UI code: engineers, designers, and PMs.
• Build and maintain the AI tooling layer for UI: Claude skills, Cursor rules, LLM-consumable documentation, or whatever meaningfully improves the quality and velocity of coding UI.
• Partner with designers, engineers, and accessibility to Improve the quality of user experience created by everyone working with the system—through advocacy, better documentation, clearer patterns, and tooling that makes the right thing the easy thing.

Who you are

• Your design craft is strong. You produce work you’re proud of and can articulate why it’s good. You hold design systems to a high bar, both in their visual expression and their technical implementation.
• You’re energized by both sides of the role. You move between design and code without treating one as a means to the other. You have a portfolio that shows both polished design work in application and production-quality libraries. 
• You are actively curious about AI-assisted development. You’ve already experimented with LLM-driven tooling, Claude skills, codegen, or similar workflows, and you have opinions about where it’s heading.
• You are able to prioritize a path forward. You have strong instincts on sequencing and know what to fix now, what to document and defer, and what to let go.
• You raise the bar around you. The best version of this role doesn’t just improve the system—it improves how everyone at Airtable builds UI. You’re motivated by that multiplier effect.

What we're looking for

• 8+ years at the intersection of design and engineering, with experience inheriting and evolving systems. 
• Deep fluency in design tokens, component architecture, theming, and accessibility standards (WCAG).
• Ability to influence through craft, clarity, and relationships.

Airtable is an equal opportunity employer. We embrace diversity and strive to create a workplace where everyone has an equal opportunity to thrive. We welcome people of different backgrounds, experiences, abilities, and perspectives. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status or any characteristic protected by applicable federal and state laws, regulations and ordinances. Learn more about your EEO rights as an applicant. 

VEVRAA-Federal Contractor

If you have a medical condition, disability, or religious belief/practice which inhibits your ability to participate in any part of the application or interview process, please complete our Accommodations Request Form and let us know how we may assist you. Airtable is committed to participating in the interactive process and providing reasonable accommodations to qualified applicants.

This is a hybrid role that will sit out of our San Francisco office. Hybrid in-office Tuesdays and Wednesdays of each week. 

About the Role

We are looking for a builder to help lead our ‘AI for Work’ efforts. Together with the Director of AI Strategy and Enablement, you will build the internal AI infrastructure that makes our teams more efficient. That means building, evaluating vendors, and continuously evolving the AI systems our teams run on with the goal of maximizing every person's efficiency and scaling our ability to deploy agents across the business. You will embed directly within business functions across the organization, deeply understand how teams operate today, and fundamentally reimagine how they should operate tomorrow. This is not about bolting automation onto existing processes; it's about redesigning how work gets done with agentic tooling transforming (and eliminating) workflows. You will partner with leaders across the business to surface high-impact opportunities, architect intelligent solutions, and deliver measurable gains in productivity, output quality, and the experiences we deliver to our employees. You will define what "AI-native operations" looks like inside Taskrabbit. 

As the AI Productivity and Business Automation Lead, you will also own a critical role in scouting, evaluating, testing, and piloting third-party AI tools to unlock significant productivity gains across Taskrabbit. You’ll work closely with the Director of AI Strategy and Enablement and functional leads to map high-value process bottlenecks and identify AI solutions. You’ll also help create structured experiments and pilot programs that demonstrate measurable business impact. In addition, you’ll help bring cutting-edge AI technology into practical application, supporting implementation and tracking success to drive our AI Strategic Plan. 

You will be responsible for "mining" the business for efficiency opportunities while simultaneously helping to build the centralized orchestration layer that ensures our enterprise AI spend is governed, consistent, and scalable. This is a high-impact IC role designed for a "scrappy builder" who thrives on turning internal complexity into streamlined, automated excellence. 

What You Will Do: 

• Partner multiple functional leaders to define new standards for how teams operate in an AI-augmented environment. Reporting to the Director of AI Strategy and Enablement, you will establish the "AI-first" baseline for daily execution, ensuring that ways of working are clearly defined and consistent across all non-engineering functions. 
• Conduct structured discovery, shadowing teams, interviewing stakeholders, and mapping end-to-end processes, to identify where AI can eliminate, redesign, or dramatically accelerate work 
• Embed within internal business functions to develop a deep, firsthand understanding of current workflows, pain points, and decision-making processes to map high-value process bottlenecks. 
• Reimagine workflows from first principles rather than automating existing steps; challenge assumptions about what requires human involvement and what doesn't
• Design, build, and deploy AI-powered automations, agents, and internal tools that reduce time spent on repetitive, low-value-add tasks while improving the quality and consistency of outputs 
• Integrate large language models, agentic frameworks, and automation platforms into internal workflows with appropriate guardrails, error handling, and human-in-the-loop checkpoints
• Measure everything: establish baselines before intervention, track adoption and usage patterns post-deployment, and quantify productivity impact in terms of hours saved, error rates reduced, and cycle times compressed 
• Serve as a trusted advisor to functional leaders on what AI can and cannot do for their teams; translate business problems into technical solutions and technical constraints into business language 
• Stay abreast of the rapidly evolving AI tooling landscape (e.g., LLM capabilities, orchestration frameworks, RPA-to-AI convergence, no-code/low-code platforms) and calibrate our internal stack accordingly 
• Build reusable patterns, templates, and playbooks so that successful automations in one function can be adapted and scaled across others 
• Collaborate closely with the engineering and product organizations to ensure internal automation efforts align with our broader technology strategy and do not create shadow IT risk 
• Help to define the framework for evaluating the success and health of our workforce transformation. You will determine the key signals that demonstrate progress, partnering with Finance and Data Science to ensure that operational shifts deliver validated value to Taskrabbit. 
• You will focus on moving beyond tool adoption to fundamental change, ensuring our teams are positioned to focus on high-value, high-judgment work that drives enterprise performance. 
• Beyond individual projects, you will focus on helping to build the mindset and capability for teams to lead their own evolution. You will create the models that allow the organization to stay agile, ensuring the workforce can continuously adapt as technology and market conditions change. 

Skills Required: 

• Educational Foundation: You hold a Bachelor’s degree in Computer Science or a comparable technical field, with demonstrated interest in Business Analytics, Finance, Data Science, applied AI, or related disciplines. 
• Experience: You bring 5+ years of professional experience, including 1–2 years of direct, relevant experience in AI, data, or analytics-driven roles. 
• GenAI Fluency: You have hands-on experience with generative AI tools (e.g., Gemini, ChatGPT, Claude) through professional, academic, or personal projects, with a strong understanding of concepts such as state management and prompt versioning. 
• AI & ML Knowledge: You possess a solid understanding of AI technologies and machine learning concepts, and can apply them effectively in business contexts.
• Analytical Thinking: You demonstrate a strong analytical mindset, with the ability to design experiments, interpret metrics, and distinguish meaningful signals from noise.
• Communication Skills: You communicate clearly and concisely, translating complex technical insights into actionable recommendations for non-technical stakeholders.
• Ownership & Drive: You exhibit curiosity, a bias for action, and a strong sense of ownership in fast-moving, ambiguous environments. 
• Hands-on Builder Mindset: You are a scrappy, execution-oriented builder who can take ideas from stakeholders and independently develop working agentic workflows without relying on external engineering resources. 
• Business Acumen: You translate complex AI capabilities into clear business value, articulating ROI and impact for diverse stakeholders. 
• Operational Excellence: You bring rigor to operations, including managing vendor relationships, forecasting technical costs (e.g., token usage), and maintaining system reliability and SLAs. 
• Strategic AI Perspective: You stay current with rapid advancements in AI (e.g., LLMs, agents), proactively identifying implications for business and workforce transformation. You effectively bridge the gap between what is technically possible and what is practically scalable. 
• Leadership & Influence: You are a self-starter who thrives in ambiguity and can lead high-stakes discussions with senior leaders, using structured thinking and compelling storytelling to drive alignment and change. 
• Impact Orientation: You are deeply data-driven, partnering effectively with Finance and Data Science to define success metrics and ensure initiatives deliver measurable productivity gains and business impact. 
• Continuous Learning: You demonstrate strong intellectual curiosity and a commitment to continuous learning, staying ahead of emerging technologies to ensure long-term organizational readiness.

Compensation & Benefits: 

At Taskrabbit, our approach to compensation is designed to be competitive, transparent, and equitable. Total compensation consists of base pay + bonus + benefits + perks. The base pay range for this position is $192,000 - $250,000. This range is representative of base pay only, and does not include any other total cash compensation amounts, such as company bonus or benefits. Final offer amounts may vary from the amounts listed above and will be determined by factors including, but not limited to, relevant experience, qualifications, geography, and level.

About the role

As part of our growing Data Science and Analytics team, you will play an instrumental role in our company’s mission of building safe and beneficial artificial intelligence by driving data-informed decision making across our organization. You’ve worked in cultures of excellence in the past, and are eager to apply that experience to help shape the cultural norms and best practices of a growing data science team as Anthropic continues to scale. In this unique company, technology, and moment in history, your work will be critical to informing our strategy as we deploy safe, frontier AI at scale to the world.

Responsibilities:

• Define core metrics, build measurement frameworks, and maintain core reporting to evaluate success
• Deep dive into product and user data to derive actionable insights and size opportunities to improve products, strategy and operations, influencing roadmaps through your insights and recommendations
• Develop hypotheses, apply rigorous causal inference methods – controlled experiments, synthetic controls –  and analyze the results in order make actionable recommendations 
• Investigate anomalies, conduct root cause analyses, and provide data-driven insights to guide priorities and inform decisions
• Build statistical models, optimization frameworks, and simulations to automate decision-making and operational processes
• Present complex technical analyses and recommendations to both technical and non-technical stakeholders
• Establish foundational data practices and help scale our analytics infrastructure to support rapid iteration and decision-making as our products grow

You may be a good fit if you have:

• 7+ years of experience in data science or analytics roles 
• Deep expertise with Python, SQL, and data visualization tools
• Expertise with experimental design, causal inference, statistical modeling, and A/B testing frameworks, particularly in high-scale technical environments
• Highly effective written communication and presentation skills
• A track record of translating complex data into clear, actionable insights for both technical and business stakeholders
• A bias for action and ability to thrive in ambiguous, fast-moving environments where you must create clarity and drive forward progress
• A passion for the company’s mission of building helpful, honest, and harmless AI
• Some experience with AI/ML products, large language models, or developer tools in the AI/ML ecosystem

We’re hiring across multiple pillars

Applying for this role will allow you to be considered for all pillars currently hiring. You will be asked to select a preference when submitting an application.

Claude Code

This role is embedded with the Claude Code product team, driving data-informed decisions for Anthropic's agentic coding tool that enables developers to delegate coding tasks directly to Claude from their terminal. You'll help the team understand how developers interact with AI coding assistants, measure developer productivity and product quality, and identify opportunities to innovate the developer experience as the product scales. Key focus areas include developer usage patterns across the platform, driving adoption within the developer ecosystem, and developer segmentation.

Strong candidates may have:

• Deep familiarity with software development workflows, developer tools, and engineering productivity metrics—ideally from working at developer-focused companies or on products targeting software engineers
• Experience analyzing human-AI interaction patterns, particularly in code generation or developer tooling contexts
• Experience supporting product teams building for the Enterprise

Consumer Data Scientist

You will be embedded with our Consumer product team. This team is responsible for building all consumer-facing Claude experiences—including web, mobile, desktop, and browser extensions. In this role, you'll shape how millions of users interact with Claude daily, driving product insights to product recommendations for interfaces that are intuitive, responsive, and push the boundaries of what AI-powered applications can be.

Strong candidates may have:

• Experience working closely with Product and Engineering teams on consumer products across multiple platforms (web, iOS, Android, desktop, browser extensions)
• Demonstrated impact on product roadmap and strategy from data deep dives in consumer growth, engagement and retention
• Expert in experimentation, holding a high statistical bar for measuring the impact of core product changes

Platform Product Data Scientist

You will partner closely with product, engineering, and go-to-market teams to understand how developers and enterprise customers build on and adopt the Claude Developer Platform—spanning our core API, agent orchestration, tool and MCP integrations, and knowledge management capabilities. You'll identify growth opportunities, surface insights about how AI agents are being built and deployed at scale, and drive data-informed decisions that shape our platform roadmap.

Strong candidates may have:

• 3+ years of experience working closely with Product or Engineering teams on API or developer-facing products, with demonstrated impact on product roadmap and strategy
• Experience supporting B2B sales teams with data insights
• Strong instincts for what drives product adoption, engagement, and retention

Model Experience Data Scientist

You will work closely with product, engineering, and research leaders to bring data-driven rigor to every phase of model development and launch. Sitting at the true bleeding edge of putting frontier AI research into the public domain, you will leverage data from both external customers and internal testing to define and measure key company success metrics, and analyze user and model behavior to identify new opportunities to push the frontier. 

Strong candidates may have:

• 3+ years of experience deeply embedding in Product or Research teams, preferably working with LLM or AI products
• Comfort working with unstructured data

Tax Planning Senior Manager

The Global Tax Team is seeking a dedicated tax professional who will play a hands-on role in a growing tax function. As Reddit continues to mature as a public company, this person will play a critical role in our strategic tax planning function, acting as a high-impact advisor to Finance and other cross functional teams. In keeping with Reddit values, the successful leader in this role is someone who operates with an open mindset and “values the human” in all interactions. This position will report to the Global Tax Director.

 Responsibilities:

• Lead the Company’s tax planning strategy and execution
• Own the global cash tax and ETR forecasting process and collaborate with Finance partners to model tax impact of business trends.
• Drive efforts to maximize tax incentives and mitigate risk
• Oversee global tax due diligence for M&A transactions and partner with Corporate Development team to model deal structures and manage post-acquisition integration
• Review and negotiate commercial agreements for tax terms and indemnifications
• Assist the provision team with preparation of quarterly and annual income tax provisions
• Design and implement tax process improvements/tax automation
• Monitor global tax legislative developments and research tax laws and policies to evaluate their tax impact
• Collaborate with business partners on ad hoc projects and provide guidance on tax related matters

Qualifications:

• Bachelor’s Degree in Accounting, Finance, or related field required, masters in tax (MST or LLM) preferred
• JD and/or CPA required
• 9+ years of corporate tax experience with at least 5 years of public accounting experience. Must have in-house experience, preferably in the tech sector
• Demonstrated expertise in accounting for income taxes, M&A and deal review processes, and US international tax regulations
• Proficiency in Excel, MS Office, and Google Workspace (e.g. Google Sheets and Slides) required, experience with Alteryx a plus
• Able to work independently under time pressure, prioritize a high workload, and meet strict deadlines
• Possess excellent attention to detail, organizational, problem solving, and prioritization skills 
• Excellent verbal and written communication skills and the ability to work collaboratively across teams in a remote environment
• Team player with a positive attitude and open mindset, not afraid to roll up your sleeves and work in a dynamic environment

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave 

About the Role:

We are building AI-powered, agentic workflows to transform how service operations scale, resolve customer needs, and maintain quality in high-stakes environments. At Gusto, that means designing systems that can earn the trust of small business owners — where a wrong answer or a missed escalation has real consequences.

As an AI Solutions Architect, you will own the end-to-end design and performance of these workflows in production — where models, tools, data, and human judgment come together to deliver outcomes. This is not a traditional architecture role. You will design, prototype, deploy, and continuously improve AI-driven systems that directly impact customer experience and operational efficiency. You will also play a key role in shaping the evolution of our AI platform by identifying capability gaps, prototyping solutions, and informing the primitives required to scale agentic systems effectively.

You will report into the Service Transformation org and work at the intersection of AI governance, service quality, and operational transformation — operating as the connective tissue between Engineering, CX, Legal, and Compliance as Gus, Gusto's AI assistant, scales.

About the Team:

The mission of our Service Transformation (CXT) team is to quickly evolve and scale how Gusto delivers outstanding service experiences and leverages AI to do so. Our team designs the systems, governance frameworks, and feedback loops that allow Gusto's service model to improve continuously, operate reliably, and earn the trust of the customers and employees who depend on it.

Here’s what you’ll do day-to-day:

• Architect, prototype, and own end-to-end agentic service workflow frameworks, from scoping through production deployment and iteration — including solve and assist targets, HITL protocols, override logic, and downstream quality safeguards
• Analyze SOPs, operational metrics and interaction data to identify and prioritize high-impact automation opportunities based on volume, risk, and customer impact
• Design and implement multi-agent orchestration patterns across tools, data sources, and decision steps within a single end-to-end workflow
• Apply and influence AI platform capabilities in partnership with CoreX (Gusto's AI Platform team) — including orchestration, retrieval, and evaluation — helping define what needs to be built to support production workflows at scale
• Identify platform gaps, prototype workflow-level solutions, and partner with engineering to shape the primitives required for reliable, scalable AI systems
• Serve as the primary CX voice in Legal, Security, Compliance, and CoreX forums — translating CX quality stakes and workflow risk into terms each audience acts on, and ensuring governance requirements are embedded in design, not retrofitted after launch
• Strengthen evaluation frameworks and feedback loops to ensure quality, compliance, and continuous improvement; contribute to Gusto's human evaluation programs and AI governance practices through deep partnership with our internal CX Labs team
• Partner with Data teams to define and track workflow performance — including solve and assist rate, AHT, rework rate, and customer effort score — clearly distinguishing between model-level, workflow-level, and operational drivers
• Build ROI models to quantify workflow impact across efficiency, quality, and cost before and after deployment
• Represent workflow performance and risk to senior stakeholders with appropriate precision and brevity; communicate in a way that drives action, not overwhelm
• Lead through ambiguity and rapid change: the function is still being defined, and you will help define it

Here’s what we're looking for:

• 8+ years in operations, product, or AI roles — with at least 2 years designing and deploying AI-assisted or agentic workflows
• Strong fluency with LLM systems, including prompt design, evaluation, and production behavior at scale
• Hands-on experience with agentic tooling, orchestration frameworks, or MCP-style integrations — conceptual familiarity is not sufficient at this level
• Experience designing human-in-the-loop (HITL) systems with clear escalation logic, override controls, and compliance-aware checkpoints
• Working knowledge of multi-agent systems and tool coordination
• Strong operational judgment: able to define and diagnose workflow metrics 
• Proven track record influencing cross-functional stakeholders — including Product, Engineering, Legal, Security, and Compliance — in writing, in design reviews, and in high-stakes forums
• Familiarity with Responsible AI practices, governance, and risk management in production environments
• Proven ability to operate in high ambiguity, create clarity, and drive alignment across technical and non-technical audiences
• Strong systems thinking with a bias toward execution and measurable outcomes
• Deep empathy for small business customers and the employees who serve them

Our cash compensation amount for this role is $133,470/yr to $173,511/yr in Denver & most major metro locations, and $157,145/yr to $204,289/yr for San Francisco & New York. Final offer amounts are determined by multiple factors including candidate location, experience and expertise and may vary from the amounts listed above.

About The Role

The AI team is building cutting-edge solutions that bring the power of AI directly to edge devices while seamlessly integrating with cloud infrastructure. We are looking for a Software Engineer to design and develop high-performance, scalable services to support AI workloads across edge and cloud environments.

What You Might Do

• Contribute to design, build, and maintain services that power AI-driven applications, ensuring scalability and performance.
• Develop APIs and microservices that facilitate seamless integration between cloud-based AI models and edge devices.
• Optimize data pipelines and storage solutions for real-time AI inference and processing.
• Work closely with AI researchers, infrastructure engineers, and frontend developers to deliver end-to-end AI-driven solutions.
• Build and optimize an agent orchestration runtime that enables tool use, memory management, and multi-step reasoning across LLMs, APIs, and edge-connected systems.
• Support the implementation of security and privacy best practices for distributed AI systems.

Essential Qualifications

• Requires at least Masters in Computer Science, Engineering, Data Science, Artificial Intelligence or related fields.
• 1+ years of experience in backend software development, with strong proficiency in Python, Java, and C++. 
• Working knowledge in LLM integration into multi-agent systems with strong understanding of agent orchestration, tool use, and memory/context management.
• Comfortable tinkering with LLMs via prompting and experienced with tools use, task decomposition, and structured outputs.
• Familiarity with database management systems (SQL and NoSQL) and data streaming technologies.
• Strong problem-solving skills and ability to work in a fast-paced, agile environment.

Preferred Skills

• Experience with AI model deployment and integration into backend services.
• Exposure to cloud-edge hybrid architectures and distributed AI workloads.
• Familiarity with on-device AI frameworks such as PyTorch, TensorFlow Lite, ONNX Runtime, or CoreML.

Salary Range: $127,000 - $175,000

About the Role:

This role is part of our Maker Program, an 18-month rotational experience designed for early-career talent looking to build foundational skills across marketing, creative, and consumer-facing functions.

The Analytics Development role sits within our Marketing Data Science team and is part of a broader rotational program within the marketing organization that will give people the opportunity to work on a wide range of impactful projects.

In this role, you will develop tools and automate workflows that join analytics capabilities with real-world needs — making Tubi's most important growth playbooks faster, more consistent, and more seamless to execute. You'll write code in Python/SQL and other languages using tools such as Cursor or Claude Code, build and manage AI agents that handle high-volume analytics and operational workflows, and work shoulder-to-shoulder with growth marketers, data scientists, and business stakeholders.

What You'll Do:

• Build and improve internal tools, automations, and lightweight applications that support recurring analytical and operational workflows across Growth Marketing
• Write production-ready Python and SQL to power data workflows, self-serve tooling, and decision-support systems
• Develop systems that automate repeatable analytical tasks, reduce manual work, and improve speed and consistency across key growth playbooks
• Use AI and LLM-based tools where appropriate to support analytics, workflow automation, and stakeholder-facing solutions
• Partner closely with Marketing Data Science, Growth Marketing, and data engineering teams to identify high-leverage opportunities for automation and tool development
• Help design workflows that connect business questions to usable data, analysis, and recommendations more quickly
• Evaluate emerging tools and technical approaches that can improve the speed, quality, or scalability of analytics work
• Contribute to best practices for building reliable, maintainable tools in a fast-moving, data-driven environment

Your Background:

• Up to three years of combined professional experience, including internships; recent graduates welcome
• Technical degree (CS, data science, statistics, engineering, math, or similar) preferred but not required
• Strong foundation in Python and comfort writing code for automation, data processing, or internal tooling
• Comfort with SQL, data manipulation, and thinking in terms of data flows
• Exposure to cloud tooling, workflow orchestration, or ML/analytics platforms is a plus
• Strong business curiosity — you want to understand why a stakeholder is asking a question, not just answer it

Program Eligibility Requirements:

• Application Deadline: May 15, 2026
• Program Timeline: Minimum 18-month commitment, starting Aug 2026, after which successful participants will transition into non-rotational full-time roles
• Work Schedule: Full-time, hybrid in San Francisco with office day requirements. Relocation assistance will not be provided.
• Work Authorization: Must have U.S. work authorization; we are unable to sponsor visas for this program
• Committed and available to work for the entire 18-month length of the program

• Navigate diverse marketing and creator functions by rotating through different teams to see how an idea moves from a concept to consumer.
• Build a toolkit of skills through direct participation in real-time projects and team-based assignments, with a particular focus on building with AI tools.
• Expand your professional network by collaborating with mentors and peers across the organization to better understand Tubi’s unique brand culture.

#LI-SY1 

#LI-Hybrid 

About the Role
We are seeking a Biomedical AI Engineer to design and deploy agentic AI systems that can reason over biomedical knowledge, plan multi-step analyses, and autonomously integrate diverse scientific data sources to accelerate therapeutic discovery.

This role goes beyond traditional LLM + RAG pipelines. You will build AI agents that can retrieve, synthesize, evaluate, and act on biomedical information across literature, omics datasets, and clinical records operating as intelligent systems embedded within discovery workflows.

Key Responsibilities

• Design and implement agentic AI architectures capable of multi-step reasoning, planning, and tool use in biomedical contexts.
• Develop LLM-based agents that dynamically retrieve, rank, and synthesize knowledge from scientific literature, knowledge graphs, omics datasets, and clinical data.
• Build memory and feedback mechanisms that allow agents to refine hypotheses, update context, and adapt to evolving data.
• Integrate external tools (analysis pipelines, simulation engines, statistical models, databases) into autonomous agent workflows.
• Architect scalable systems that combine structured and unstructured biomedical data within production-grade AI environments.
• Collaborate closely with computational biologists, translational scientists, and software engineers to embed agentic systems into real-world discovery pipelines.
• Evaluate robustness, reliability, and interpretability of autonomous systems in high-stakes biomedical settings.

Qualifications

• Degree in Computer Science, Machine Learning, Computational Biology, Biomedical Informatics, or related field.
• Strong hands-on experience with large language models, including fine-tuning, alignment, and structured prompting.
• Experience building agent-based systems or complex LLM orchestration frameworks (e.g., multi-agent systems, tool-using LLMs, planning modules).
• Proficiency in Python and modern ML frameworks (PyTorch, JAX, TensorFlow).
• Experience working with large-scale biomedical datasets (genomics, transcriptomics, clinical records, or scientific corpora).

Preferred

• Experience designing autonomous research assistants or AI systems that perform multi-step scientific reasoning.
• Familiarity with knowledge graphs, hybrid symbolic-neural systems, or multimodal foundation models.
• Understanding of privacy, security, and regulatory considerations in healthcare AI.

Compensation

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity. The base pay range for this position is expected to be $190,000 - $280,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

About the Role

We are a technology-driven biotechnology company using AI to compress the timelines of drug discovery and development. At Xaira, we believe that becoming a truly AI-native organization is not a future ambition. It is a present imperative. The way we build our infrastructure, adopt our tools, and lead our technology function will determine how fast we can move and how far we can go.The optimal candidate is energized and enthused to push the frontier of what an enterprise can do with all available and evolving AI tools.

We are seeking a VP of Information Technology to serve as the senior-most IT leader and AI evangelist on the team. The optimal candidate is energized and enthused to push the frontier of what an enterprise can do with all available and evolving AI tools.This role will own the full scope of IT: strategy, security, infrastructure, operations, and the team that delivers it all. You will set the technology direction for Xaira, build a high-performing function, and be accountable for outcomes across the organization.

This is a role for an experienced leader who understands that in a company like ours. It is not a support function. It is the infrastructure on which scientific breakthroughs are built. You will be the architect of an AI-native enterprise, embedding intelligence into how we operate, how we discover, and how we scale. You will enable our team to move faster, work smarter, and focus on what matters most: getting medicines to patients sooner.

What You'll Own

Technology Strategy & Architecture

• Define and own the company's IT roadmap across cloud infrastructure, enterprise applications, end-user computing, networking, and AI-powered systems purpose-built for drug discovery and development
• Make architectural decisions with long-term scalability in mind, not just near-term need
• Lead the company's AI adoption strategy across the enterprise, identifying where AI and machine learning tools can meaningfully accelerate research workflows, computational biology pipelines, and clinical operations
• Embed AI-driven automation into how the company works at every level, from IT operations and security to scientific data workflows, reducing manual overhead and giving researchers more time to do science
• Identify and adopt emerging technologies in the life sciences AI space that create meaningful competitive advantage in speed and precision

Infrastructure & Operations

• Ensure the reliability, performance, and scalability of all enterprise systems including the AI, machine learning, and high-performance computing platforms that power drug discovery
• Build and maintain cloud-first infrastructure that can support the significant compute and data demands of AI-driven research without becoming a bottleneck to scientific progress
• Own incident management processes including root cause analysis, post-mortems, and follow-through on remediation
• Establish and enforce SLAs, OKRs, and operational standards with clear accountability

Security

• Serve as the company's senior security leader in the absence of a CISO, owning the full security posture across network, endpoint, identity, cloud, and application layers
• Lead all compliance programs including SOC 2, ISO 27001, GDPR, CCPA, and applicable life sciences regulatory requirements
• Build a proactive security culture that encompasses threat modeling, vulnerability management, incident response, and employee awareness
• Report regularly to executive leadership and the board on risk, security posture, and mitigation plans
• Make informed decisions on the trade-offs between operational speed and security risk

Team Leadership

• Recruit, develop, and retain a strong IT organization with the depth to scale alongside the business
• Build a culture of accountability, professional growth, and operational excellence
• Develop strong internal talent and succession planning so the organization is resilient at every level

Executive Partnership

• Act as a trusted technology advisor to the CEO, CFO, and broader leadership team
• Partner with Engineering, Finance, Legal, People, and Operations to ensure IT functions as a strategic business enabler
• Communicate technical strategy and risk in clear, accessible terms for non-technical stakeholders

Vendor & Financial Management

• Own and manage the IT budget with a focus on both fiscal discipline and strategic investment
• Develop and manage key vendor relationships and negotiate enterprise agreements that support long-term business flexibility
• Ensure technology spending is purposeful and tied to measurable business outcomes

What We're Looking For

Required

• 15+ years of progressive IT leadership, including 5+ years as the senior IT leader (VP, CIO, or equivalent) at a high-growth technology company
• Proven experience owning both IT operations and security without a dedicated CISO
• Deep expertise across cloud platforms (GCP, AWS, or Azure), enterprise architecture, SaaS ecosystems, and modern endpoint management
• Working knowledge of cybersecurity principles, risk frameworks, and compliance programs sufficient to lead the function with credibility
• Demonstrated ability to lead effectively in uncharted territory, setting direction and adapting as the business evolves
• Strong analytical and data-driven approach to decision-making
• Excellent executive communication skills, with the ability to present to and influence a board of directors
• Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent practical experience

Preferred

• Experience at a scaled technology or life sciences company
• Proven hands-on experience with AI/ML infrastructure, LLM tooling, and intelligent automation at enterprise scale
• A track record of driving company-wide AI adoption, not just evaluating tools but leading the organizational change that makes adoption stick
• Experience scaling IT through rapid organizational growth
• CISSP, CISM, or equivalent security credential
• MBA or advanced technical degree

Leadership Competencies

• Strategic Vision Translates complex business and scientific goals into a clear, actionable IT roadmap. Anticipates organizational needs and makes technology investments that deliver long-term value.
• People Leadership Builds, develops, and retains high-performing teams. Creates an environment where people do their best work through clarity of direction, coaching, and genuine investment in career growth.
• Operational Excellence Holds a high bar for reliability, efficiency, and continuous improvement. Establishes the processes, metrics, and accountability structures that keep the organization running at its best.
• Security & Risk Management Owns the company's security posture end to end. Makes sound, defensible decisions on risk in a regulated, data-sensitive environment and communicates clearly to executive leadership.
• Communication & Influence Earns trust and drives alignment across the organization, from the lab bench to the boardroom. Able to make technical complexity understandable and compelling to any audience.

Compensation

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity.  The base pay range for this position is expected to be $300,000 - $325,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

The role:

SoFi’s Staff AI Engineer is a highly experienced, hands-on individual contributor within SoFi’s growing independent risk organization, focused on owning the design, development, and evolution of agentic AI systems to solve real-world, high-impact problems.

This role will be instrumental in architecting, building, and scaling AI systems that enhance risk management and internal workflows, with a focus on creating reliable, reusable, and production-grade solutions.

This role operates at the intersection of the intelligence layer, including LLMs, agents, and orchestration, and the experience layer, which defines how users interact with and derive value from AI systems. You will shape how these systems are designed and integrated into critical workflows, ensuring they are intuitive, reliable, and effective in high-stakes risk environments.

You will work closely with the Senior Manager of AI Engineering as well as business stakeholders, to translate complex, ambiguous problems into scalable, production-grade AI systems with measurable impact.

What you’ll do: 

• Architect and Develop Agentic AI Systems: Lead the design and development of AI systems that leverage multi-step reasoning, tool use, and structured workflows, using frameworks such as LangGraph or similar approaches. Incorporate planning, memory, tool integration, and adaptive control flow to enable automated decisioning, risk insights, and internal platforms.
• Design the Experience Layer: Define how users interact with AI systems by designing workflows, interfaces, and feedback loops that drive adoption, usability, and trust. THis will involve close coordination with users / stakeholders. Ensure alignment between system behavior and user expectations.
• Context Engineering and System Design: Define and implement approaches for structuring inputs, outputs, and system context to improve reliability and performance of LLM systems, including prompt design, retrieval strategies, and workflow composition.
• Productionize AI Systems: Develop production-grade services and APIs, integrate agents into real systems, and ensure scalability, reliability, and maintainability.
• AI Observability and Evaluation: Build tracing, debugging, and evaluation frameworks to understand system behavior and continuously improve agent performance.
• Cross-Functional Collaboration: Partner with risk, engineering, and business teams to translate ambiguous problems into working AI systems and deliver measurable outcomes.
• Proof of Concepts and Innovation: Innovation and Prototyping: Identify high-impact opportunities to apply AI, rapidly prototype solutions, and evaluate emerging tools and approaches to inform long-term system design aligned with latest trends in AI.

What you’ll need:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field.
• 7+ years of software engineering experience, with significant experience building and scaling AI-powered systems in production.
• Strong experience working with LLMs and building applications using prompting, APIs, and/or agent frameworks.
• Experience designing and implementing agentic systems, including patterns such as tool use, multi-step reasoning, and workflow orchestration.
• Deep experience in context engineering for LLM systems, including structuring inputs and outputs, prompt design, and retrieval-based approaches.
• Strong backend engineering experience, including building scalable services and APIs (Python preferred).
• Experience designing systems on cloud platforms such as AWS, Azure, or GCP, with an understanding of modern development and deployment practices.
• Experience working with structured and unstructured data, including building pipelines to support downstream AI applications.
• Experience defining and implementing evaluation frameworks for AI systems, including metrics, experimentation, and performance iteration.
• Strong system design skills, with the ability to architect scalable, reliable solutions.
• Ability to operate effectively in ambiguous problem spaces and translate them into well-defined systems.
• Strong communication and collaboration skills, with the ability to work cross-functionally and influence technical decisions.
• Demonstrated ownership mindset, with a track record of delivering high-impact systems end-to-end.

Nice to have:

• Experience designing and building user-facing workflows or internal tools powered by AI.
• Familiarity with observability and evaluation tools for AI systems such as Langfuse, LangSmith, or similar.
• Experience working in financial services or building systems for risk-related use cases.
• Experience with frontend technologies such as React for building AI-powered interfaces.
• Experience contributing to shared platforms, libraries, or internal tooling that enable reuse across teams.
• Experience building systems that require explainability, auditability, or operate in regulated environments.

This is Engineering at Lattice

At Lattice, we build software that helps people and organizations thrive. Our engineering team values maintainable systems, strong collaboration, and thoughtful product experiences.

As we expand AI-powered capabilities across our platform, security is a core part of how we design, build, and operate our product. Our Product Security team partners closely with engineering to ensure we ship features that are secure by default and resilient in production.

What You Will Do

You will work closely with product and platform engineering teams to improve the security of Lattice’s applications and services.

Product Security & Engineering Partnership

• Partner with engineers to identify, triage, and remediate security issues in product features and services
• Participate in security reviews and threat modeling for new features and systems
• Perform security-focused code reviews and help identify common vulnerabilities
• Contribute to secure-by-default patterns, libraries, and tooling in our TypeScript-based stack

Security Tooling & Operations

• Help implement and operate security tooling (SAST, DAST, dependency scanning, etc.)
• Support vulnerability management workflows, including internal findings and bug bounty reports
• Assist in investigating security issues and assessing risk and impact

Cloud & Platform Security

• Collaborate with platform and infrastructure teams to improve application and cloud security posture
• Contribute to improving security practices in AWS-based environments

AI/LLM Security

• Assist in identifying and mitigating risks in AI/LLM-powered features, including prompt injection, data leakage, and unsafe output handling
• Apply emerging best practices (OWASP Top 10 for LLM Applications) to real product use cases

Security Enablement

• • Contribute to security guidance, documentation, and training for engineering teams
  • Help improve how security is integrated into the development lifecycle

What You Will Bring to the Table

Experience that is important for you to have at some level:

• 1–3+ years of experience in product security, application security, or software engineering
• Experience writing and maintaining code in JavaScript/TypeScript (or similar languages like Python or Ruby)
• Familiarity with common web and API vulnerabilities (e.g., OWASP Top 10)
• Exposure to security testing tools (SAST, DAST, dependency scanning, etc.)
• Experience working in or with cloud environments (AWS or similar)

Technical Approach

• Ability to identify common security risks and suggest practical mitigations
• Understanding of secure coding practices and basic security controls
• Interest in how security decisions impact real-world product systems

Collaboration & Growth

• Strong communication skills and ability to work closely with engineering teams
• Willingness to ask questions, learn quickly, and take ownership of well-scoped problems
• Ability to contribute to team discussions and share security context effectively

Experience that would be nice to have:

• Experience with modern web architectures (Next.js, NestJS, GraphQL)
• Familiarity with containerization or Kubernetes
• Experience or interest in AI/LLM security, including

----

The estimated annual cash salary for this role is $116,500 - $154,000. This position is also eligible for incentive stock options, subject to the terms of Lattice’s applicable plans

Benefits: The Company offers the following benefits for this position, subject to applicable eligibility requirements: Medical insurance; Dental insurance; Vision insurance; Life, AD&D, and Disability Insurance; Emergency Weather Support; Wellness Apps; Paid Parental Leave, Paid Time off inclusive of holidays and sick time; Commuter & Parking Accounts; Lunches in the Office; Internet and Phone Stipend; 401(k) retirement plan; Financial Planning; Learning & Development Budget

*Note on Pay Transparency:

Lattice provides an estimate of the compensation for roles that may be hired as required by state regulations. Compensation may vary based on (a) location, as Lattice factors in specific location when benchmarking compensation for most roles; (b) individual candidate skills and qualifications; and (c) individual candidate experience.

Additionally, Lattice leverages current market data to determine compensation, so posted compensation figures are subject to change as new market data becomes available. The salary, other compensation, and benefits information is accurate as of the date of this posting. Lattice reserves the right to modify this information at any time, subject to applicable law.

#LI-remote

The Opportunity

The web is evolving beyond pages toward AI-powered, conversational, and agentic surfaces that change how users consume content and how publishers monetize it. Traditional ad placements and formats are no longer enough. Moloco is building the infrastructure to power next-generation monetization across these new environments bridging the open web, AI chat interfaces, and emerging content ecosystems.

We’re seeking a Director of Next Gen Publisher Monetization to lead this transformation. You’ll define how publishers capture value in the age of generative and conversational AI — designing monetization systems, formats, and signals that align with these new experiences.

The ideal candidate is a deep ad tech leader who has built or scaled publisher monetization platforms and is ready to pioneer the next frontier:  monetizing AI-driven interactions in ways that are transparent, privacy-safe, and performance-optimized.

What You’ll Do

• Define the Future of Publisher Monetization: Build Moloco’s vision and roadmap for monetization on AI chat and next-generation web surfaces.
• Reimagine the Ad Experience: Design new ad and sponsorship formats tailored for conversational, contextual, and intent-rich environments.
• Lead Publisher Strategy: Partner with leading web publishers to transition from traditional display monetization to AI-native monetization models.
• Develop AI-Powered Yield Systems: Work with data science and engineering to build models that understand context, intent, and engagement optimizing monetization dynamically across AI-driven interactions.
• Advance Privacy and Trust: Define frameworks for privacy-safe signal use and explainable monetization in AI contexts.
• Shape the Industry Narrative: Represent Moloco in defining what open, independent monetization means in the era of AI-driven content and chat.
• Build and Lead Teams: Hire, mentor, and lead a team driving innovation at the intersection of ad tech, AI, and publisher economics.

What We’re Looking For

Minimum Qualifications

• 8+ years of experience in ad tech or publisher monetization product leadership.
• Proven experience building or leading publisher monetization platforms (SSPs, ad exchanges, or ad servers).
• Deep understanding of ad serving, auction dynamics, and programmatic ecosystems.
• Passion for emerging AI surfaces: chat, generative experiences, and intelligent content interfaces.
• Strong communication and strategic leadership skills across technical, commercial, and industry stakeholders.

Preferred Qualifications

• Bachelor’s degree in Computer Science, Engineering, or a related technical field.
• Experience designing contextual and privacy-first monetization systems.
• ex-founder and experience building product from zero to 1
• Understanding of AI/LLM technologies, content generation, or recommendation systems.
• Familiarity with open web monetization challenges and the role of independent ad tech in an era of walled gardens and AI platforms.

What we do  

You’ll join a software engineering team building internal AI solutions that support teams across The Trade Desk. We leverage large language models, retrieval‑augmented generation (RAG), agentic systems, and enterprise platforms like Microsoft Copilot and Anthropic Claude to improve productivity, streamline workflows, and reduce operational friction.

Our team also plays a key role in AI enablement across the company—supporting teams as they adopt Copilot, Claude and similar tools, designing and deploying custom AI agents, and guiding partners through their AI journey from idea to impact.

As a Senior AI Engineer on this team, you’ll be an end-to-end owner—collaborating closely with stakeholders, identifying opportunities, and delivering tools that make a real impact. We’re a nimble, fast-paced, and highly collaborative group that thrives on transforming the way teams operate and driving greater value across The Trade Desk.

What you’ll do: 

Some of the work that you will be doing to help us deliver on our mission is:

• Design and deploy intelligent agentic systems that integrate large language models (LLMs) with enterprise data, tools, and workflows using frameworks like LangChain, LlamaIndex, and Semantic Kernel.
• Develop Retrieval-Augmented Generation (RAG) applications using tools like Azure AI Search, vector databases, and secure enterprise connectors to deliver contextual insights.
• Build and deploy agents using Microsoft Copilot, Copilot Studio, Anthropic Claude, and similar platforms to help teams operationalize solutions within enterprise guardrails.
• Build and iterate on conversational agents that solve real-world problems, meet stakeholder needs, and deliver measurable business value.
• Deliver high-impact features by collaborating across teams, leading through ambiguity, and aligning technical solutions with business goals.
• Drive quality and performance through automated testing, monitoring, and data-driven evaluation of success criteria, user adoption, and operational efficiency.
• Mentor teammates and contribute to a culture of innovation, technical excellence, and continuous learning.

Who you are: 

• You have a Bachelor’s/Master’s level degree in computer science or relevant engineering-related field or equivalent experience.
• You have 8-10+ years of software engineering experience, including 1-2+ years working on AI-powered systems or products.
• You are proficient in Python and comfortable with additional languages such as C#, SQL, or TypeScript/React.
• You’re excited about AI enablement, including helping teams adopt platforms like Microsoft Copilot, Anthropic Claude and Copilot Studio, building agents, and guiding others through their AI journey.
• You have a good foundational knowledge of or hands-on experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel) and prompt engineering using LLM APIs.
• You have experience productionizing applications and implementing CI/CD pipelines to ensure reliable, scalable deployments.
• You are skilled in data ingestion and transformation using APIs, ETL pipelines, and connectors, and familiar with vector databases and retrieval strategies.
• You communicate clearly across technical and non-technical audiences and thrive in a collaborative, cross-functional environment.
• You are a fast learner who adapts quickly to new technologies and solves complex problems with creativity and pragmatism.

#LI-TP1

A variety of technical opportunities is one of the best things about working at The Trade Desk as a software engineer, which is why we do not expect you to know every technology we use when you start. What we care about is that you can learn quickly and find solutions to complex problems using the optimum tools for the job. What you know is less important than how well you learn and innovate. We are not seeking engineers who know all the answers; we need engineers who can invent answers no one has thought of yet and find answers to the questions yet to be asked. 

The Trade Desk does not accept unsolicited resumes from search firm recruiters. Fees will not be paid in the event a candidate submitted by a recruiter without an agreement in place is hired; such resumes will be deemed the sole property of The Trade Desk. The Trade Desk is an equal opportunity employer. All aspects of employment will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

[LA JOBS ONLY] The Trade Desk will consider qualified applicants with criminal histories for employment in a manner consistent with the requirements of the Los Angeles Fair Chance Initiative for Hiring, Ordinance No. 184652.

[SF JOBS ONLY] Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

#LI-TP1

About the Role:

Gusto is looking for an experienced, hands-on people manager to lead a core Data Science & Analytics team. This role sits at the heart of how we use data — and increasingly AI — to understand, shape, and scale Gusto's products. You’ll both manage a team of data scientists and analysts as well as personally get in-the-weeds to work closely with Product, Engineering, Design, Marketing, Sales, and Finance to deliver insights and frameworks that inform strategy, optimize user experiences, and accelerate business growth.

We're looking for a leader who can balance strategic influence with hands-on craft — someone who can guide senior Gusto leaders through data and AI strategy, coach data scientists on impactful problem solving, and dive in to drive forward statistically rigorous analyses when needed.

Here’s what you’ll do day-to-day:

• Lead and develop a team of data scientists – hire, empower, and coach team members; set a high bar for analytical quality and career growth.
• Shape product and business strategy through data – partner with Product and cross-functional leaders to identify opportunities, prioritize investments, and influence long-term product roadmaps.
• Develop and scale measurement frameworks – define key metrics, design monitoring systems, and ensure product initiatives — including AI-powered features — are rigorously tracked and evaluated.
• Support experimentation and decision-making – support inferential analyses and experimentation (e.g., A/B tests, segmentation, funnel analysis), including designing evaluations for AI and ML-driven systems, ensuring findings are actionable and aligned to strategic goals.
• Partner on AI-powered product development – collaborate with ML Engineering and Product to bring intelligent features to life (personalization, predictions, intelligent automation), ensuring they're grounded in customer insight and measured for real-world impact.
• Balance strategic and hands-on impact – dive deep into data, review and refine analyses, and ensure insights are both technically sound and business-relevant.
• Influence senior leadership – communicate insights and recommendations clearly, framing trade-offs and shaping executive decision-making.

Here’s what we're looking for:

• 10+ years of experience in data science or related fields, with at least 4 years managing and scaling high-performing data science teams.
• Deep expertise in product analytics – experience with user acquisition, activation, retention, engagement, or expansion in SaaS or product-led environments.
• Technical fluency – advanced coding skills, strong statistical reasoning, and familiarity with experimentation frameworks; ability to mentor data scientists on best practices.
• AI product intuition – experience working at the intersection of data science and AI product development; comfort reasoning about model behavior, evaluation design, and the tradeoffs of deploying AI in customer-facing contexts.
• Strategic and business acumen – demonstrated ability to connect insights to product and business goals, and to influence roadmaps through data.
• Executive communication skills – proven experience presenting insights to senior stakeholders, turning complex data into clear and actionable recommendations.
• Cross-functional collaboration – history of working closely with Product, Engineering, and go-to-market teams to drive decisions and deliver impact.
• Hands-on experience with ML applications in product contexts (e.g., personalization, churn prediction, customer segmentation, or LLM-powered features) is strongly preferred.
• Familiarity with multi-product SaaS ecosystems and customer lifecycle analytics is desirable.

Our cash compensation amount for this role is targeted at $217,000 - $265,000 in San Francisco and New York. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.

Apply using this link. We are accepting applications on a rolling basis for the next cohort of Anthropic Fellows, which is expected to start in late September. In some circumstances, we can accommodate fellows starting outside the usual cohort timelines — please note in your application if the September start date doesn't work for you.

This page is specific to one of the Anthropic Fellows Workstreams, see also the main Anthropic Fellows posting.

Anthropic Fellows Program overview

The Anthropic Fellows Program is designed to foster AI research and engineering talent. We provide funding and mentorship to promising technical talent - regardless of previous experience.

Fellows will primarily use external infrastructure (e.g. open-source models, public APIs) to work on an empirical project aligned with our research priorities, with the goal of producing a public output (e.g. a paper submission). In one of our earlier cohorts, over 80% of fellows produced papers.

We run multiple cohorts of Fellows each year and review applications on a rolling basis. This application is for cohorts starting in July 2026 and beyond.

What to expect

• 4 months of full-time research 
• Direct mentorship from Anthropic researchers 
• Access to a shared workspace (in either Berkeley, California or London, UK)
• Connection to the broader AI safety and security research community
• Weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAD + benefits (these vary by country)
• Funding for compute (~$15k/month) and other research expenses

Interview process

The interview process will include an initial application & reference check, technical assessments & interviews, and a research discussion. 

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

Compensation

The expected base stipend for this role is 3,850 USD / 2,310 GBP / 4,300 CAD per week, with an expectation of 40 hours per week for 4 months (with possible extension).

Fellows workstreams

Due to the success of the Anthropic Fellows for AI Safety Research program, we are now expanding it across teams at Anthropic. We expect there to be significant overlap in the types of skills and responsibilities across the roles and will by default consider candidates for all the workstreams.

Some of the workstreams may include unique assessment steps; we therefore ask you for workstream preferences in the application. You can see an overview of the current workstreams below:

1. AI Safety Fellows
2. AI Security Fellows
3. ML Systems & Performance Fellows
4. Reinforcement Learning Fellows
5. Economics & Societal Impacts Fellows

This page is specific to one of the Anthropic Fellows Workstreams, see also the main Anthropic Fellows posting.

Across the workstreams, you may be a good fit if you:

• Are motivated by making sure AI is safe and beneficial for society as a whole
• Are excited to transition into empirical AI research and would be interested in a full-time role at Anthropic
• Have a strong technical background in computer science, mathematics, or physics
• Thrive in fast-paced, collaborative environments
• Can implement ideas quickly and communicate clearly

Strong candidates may also have:

• Strong background in a discipline relevant to a specific Fellows workstream (e.g. economics, social sciences, or cybersecurity)
• Experience in areas of research or engineering related to their workstream

Candidates must be:

• Fluent in Python programming
• Available to work full-time on the Fellows program

AI Security Fellows

Mentors, research areas, & past projects

Fellows will undergo a project selection & mentor matching process. Potential mentors include:

• Nicholas Carlini
• Keri Warr
• Evyatar Ben Asher
• Keane Lucas
• Newton Cheng

On our Alignment Science and Frontier Red Team blogs, you can read about some past Fellows projects, including:

• AI agents find $4.6M in blockchain smart contract exploits: Winnie Xiao and Cole Killian, mentored by Nicholas Carlini and Alwin Peng
• Strengthening Red Teams: A Modular Scaffold for Control Evaluations: Chloe Loughridge et al., mentored by Jon Kutasov and Joe Benton

Unique candidate criteria

You might be a particularly great fit for this workstream if you:

• Are motivated by reducing catastrophic risks from advanced AI systems
• Have contributed to open-source projects in LLM- or security-adjacent repositories
• Have demonstrated success in bringing clarity and ownership to ambiguous technical problems
• Have experience with pentesting, vulnerability research, or other offensive security work
• Have a demonstrated willingness to do the "dirty work" that produces high-quality outputs
• Have reported CVEs or been awarded bug bounties
• Have experience with empirical ML research projects
• Have experience with deep learning frameworks and experiment management

Logistics

Logistics Requirements: To participate in the Fellows program, you must have work authorization in the US, UK, or Canada and be located in that country during the program.

Workspace Locations: We have designated shared workspaces in London and Berkeley where fellows will work from and mentors will visit. We are also open to remote fellows in the UK, US, or Canada. We will ask you about your availability to work from Berkeley or London (full- or part-time) during the program.

Visa Sponsorship: We are not currently able to sponsor visas for fellows. To participate in the Fellows program, you need to have or independently obtain full-time work authorization in the UK, the US, or Canada.

Program Duration: The program runs for 4 months, full-time. If you can't commit to the full duration, please still apply and note your constraints in the application. We review these requests on a case-by-case basis.

Please note: We do not guarantee that we will make any full-time offers to fellows. However, strong performance during the program may indicate that a Fellow would be a good fit for full-time roles at Anthropic. In previous cohorts, 25-50% of fellows received a full-time offer, and we’ve supported many more to go on to do great work on AI safety and security at other organizations.

Applications and interviews are managed by Constellation, our recruiting partner. Clicking "Apply here" will take you to their portal, and updates will come from a Constellation address. Constellation also runs the Berkeley workspace and provides program support for fellows working on AI safety and security; fellows on capabilities-focused projects are supported directly by Anthropic. All applicants currently use the same application portal but we are working to separate applications for safety/security and capabilities focused projects in future rounds.

Apply here

The below are Anthropic's policies for full time roles. These do NOT apply to the Fellows Program.

Apply using this link. We are accepting applications on a rolling basis for the next cohort of Anthropic Fellows, which is expected to start in late September. In some circumstances, we can accommodate fellows starting outside the usual cohort timelines — please note in your application if the September start date doesn't work for you.

Anthropic Fellows Program overview

The Anthropic Fellows Program is designed to foster AI research and engineering talent. We provide funding and mentorship to promising technical talent - regardless of previous experience.

Fellows will primarily use external infrastructure (e.g. open-source models, public APIs) to work on an empirical project aligned with our research priorities, with the goal of producing a public output (e.g. a paper submission). In one of our earlier cohorts, over 80% of fellows produced papers.

We run multiple cohorts of Fellows each year and review applications on a rolling basis. This application is for cohorts starting in July 2026 and beyond.

What to expect

• 4 months of full-time research 
• Direct mentorship from Anthropic researchers 
• Access to a shared workspace (in either Berkeley, California or London, UK)
• Connection to the broader AI safety and security research community
• Weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAD + benefits (these vary by country)
• Funding for compute (~$15k/month) and other research expenses

Interview process

The interview process will include an initial application & reference check, technical assessments & interviews, and a research discussion. 

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

Compensation

The expected base stipend for this role is 3,850 USD / 2,310 GBP / 4,300 CAD per week, with an expectation of 40 hours per week for 4 months (with possible extension).

Fellows workstreams

Due to the success of the Anthropic Fellows for AI Safety Research program, we are now expanding it across teams at Anthropic. We expect there to be significant overlap in the types of skills and responsibilities across the roles and will by default consider candidates for all the workstreams.

Some of the workstreams may include unique assessment steps; we therefore ask you for workstream preferences in the application. You can see an overview of the current workstreams below:

1. AI Safety Fellows
2. AI Security Fellows
3. ML Systems & Performance Fellows
4. Reinforcement Learning Fellows
5. Economics Fellows

Across the workstreams, you may be a good fit if you:

• Are motivated by making sure AI is safe and beneficial for society as a whole
• Are excited to transition into empirical AI research and would be interested in a full-time role at Anthropic
• Have a strong technical background in computer science, mathematics, or physics
• Thrive in fast-paced, collaborative environments
• Can implement ideas quickly and communicate clearly

Strong candidates may also have:

• Strong background in a discipline relevant to a specific Fellows workstream (e.g. economics, social sciences, or cybersecurity)
• Experience in areas of research or engineering related to their workstream

Candidates must be:

• Fluent in Python programming
• Available to work full-time on the Fellows program

AI Safety Fellows

Mentors, research areas, & past projects

Fellows will undergo a project selection & mentor matching process. Potential mentors include:

• Sam Bowman
• Sara Price
• Alex Tamkin
• Nina Panickssery
• Trenton Bricken
• Logan Graham
• Jascha Sohl-Dickstein
• Joe Benton
• Fabien Roger
• Samuel Marks
• Kyle Fish
• Ethan Perez

Note: You may research mentors' prior work, but all applications must go through the official form, not the mentors.

Our mentors will lead projects in select AI safety research areas, such as:

• Scalable Oversight: Developing techniques to keep highly capable models helpful and honest, even as they surpass human-level intelligence in various domains.
• Adversarial Robustness and AI Control: Creating methods to ensure advanced AI systems remain safe and harmless in unfamiliar or adversarial scenarios.
• Model Organisms: Creating model organisms of misalignment to improve our empirical understanding of how alignment failures might arise.
• Model Internals / Mechanistic Interpretability: Advancing our understanding of the internal workings of large language models to enable more targeted interventions and safety measures.
• AI Welfare: Improving our understanding of potential AI welfare and developing related evaluations and mitigations.

On our Alignment Science and Frontier Red Team blogs, you can read about past projects, including:

• Subliminal Learning: Language Models Transmit Behavioral Traits via Hidden Signals in Data: Alex Cloud and Minh Le, et al., mentors including Samuel Marks and Owain Evans
• Open-source circuits: Michael Hanna and Mateusz Piotrowski with mentorship from Emmanuel Ameisen and Jack Lindsey

For a full list of representative projects for each area, please see these blog posts: Introducing the Anthropic Fellows Program for AI Safety Research, Recommendations for Technical AI Safety Research Directions.

Unique candidate criteria

You might be a particularly great fit for this workstream if you:

• Are motivated by reducing catastrophic risks from advanced AI systems
• Have experience with empirical ML research projects
• Have experience working with large language models
• Have experience in one of the research areas mentioned above
• Have a track record of open-source contributions

AI Security Fellows

Mentors, research areas, & past projects

Fellows will undergo a project selection & mentor matching process. Potential mentors include:

• Nicholas Carlini
• Keri Warr
• Evyatar Ben Asher
• Keane Lucas
• Newton Cheng

On our Alignment Science and Frontier Red Team blogs, you can read about some past Fellows projects, including:

• AI agents find $4.6M in blockchain smart contract exploits: Winnie Xiao and Cole Killian, mentored by Nicholas Carlini and Alwin Peng
• Strengthening Red Teams: A Modular Scaffold for Control Evaluations: Chloe Loughridge et al., mentored by Jon Kutasov and Joe Benton

Unique candidate criteria

You might be a particularly great fit for this workstream if you:

• Are motivated by reducing catastrophic risks from advanced AI systems
• Have contributed to open-source projects in LLM- or security-adjacent repositories
• Have demonstrated success in bringing clarity and ownership to ambiguous technical problems
• Have experience with pentesting, vulnerability research, or other offensive security work
• Have a demonstrated willingness to do the "dirty work" that produces high-quality outputs
• Have reported CVEs or been awarded bug bounties
• Have experience with empirical ML research projects
• Have experience with deep learning frameworks and experiment management

ML Systems & Performance Fellows

Mentors, research areas, & past projects

Fellows will undergo a project selection & mentor matching process. Potential mentors include:

• Alwin Peng
• Zygi Straznickas

For a past example of an engineering-heavy project, see:

• AI agents find $4.6M in blockchain smart contract exploits

Projects in this workstream may include:

• Building a CPU simulator for accelerator workloads
• Adding backends for different accelerators on an open source project
• Building on demand infrastructure for other infrastructure heavy fellows projects 
• Building complex synthetic data or environment pipelines

Unique candidate criteria

You might be a particularly great fit for this workstream if you:

• Have strong software engineering skills with experience building complex ML systems
• Can balance research exploration with engineering rigor and operational reliability
• Enjoy collaborating across research and engineering disciplines
• Are comfortable working with large-scale distributed systems and high-performance computing (e.g. in trading)
• Have experience with training, fine-tuning, or evaluating large language models
• Are adept at analyzing and debugging model training processes

Reinforcement Learning Fellows

Mentors, research areas, & past projects

Fellows will undergo a project selection & mentor matching process. Potential research areas and mentors include:

• Ruhua Jiang
• Kaidi Cao
• Sunny Duan
• David Brandfonbrener
• Colt Steele
• Dino Distefano
• Will Williams

Projects in this workstream may include:

• Building model-based tools to better understand AI training data and improve training data quality
• A research project to better understand generalization
• Creating RL environments to improve Claude models at capabilities that are within your domain of expertise
• Building RL environments for safety-related tasks
• Conducting research and implementing solutions in areas such as RL algorithms

Unique candidate criteria

You might be a particularly great fit for this workstream if you:

• Have strong software engineering skills with experience building complex ML systems
• Can balance research exploration with engineering rigor and operational reliability
• Enjoy collaborating across research and engineering disciplines
• Are comfortable working with large-scale distributed systems and high-performance computing
• Have experience with training, fine-tuning, or evaluating large language models
• Are adept at analyzing and debugging model training processes

The Anthropic Institute Fellows (Economics & Policy)

Mentors, research areas, & past projects

Fellows will undergo a project selection & mentor matching process. Potential research areas and mentors include:

• Economics
  • Maxim Massenkoff
  • Peter McCrory
• Policy, Security, and Society
  
  • Jack Clark
  • Marina Favaro
  • Jim Baker

Projects in this workstream may include:

• Designing and conducting empirical research on AI's economic effects, drawing on external data sources
• Developing new methodological approaches for studying AI's impact on labor markets, the future of work, and society
• Analysing the offense–defense balance for AI-enabled cyber and bio capabilities as models scale
• Measuring the extent to which model performance increases with custom harnesses?
• Identifying market driven mechanisms that could improve societal resilience to anticipated threats from AI systems?
• Identifying which metrics relating to AI R&D could service as early warning signals for recursive self-improvement

For past project examples, see:

• How AI Impacts Skill Formation: Judy Shen and Alex Tamkin
• Stress-Testing Model Specs Reveals Character Differences among Language Models: Jifan Zhang, Henry Sleight, Andi Peng, John Schulman, and Esin Durmus

Unique candidate criteria

You might be a particularly great fit for this workstream if you:

• Have an interest in economics or policy research; prior experience in this area is a plus but not required
• Are adaptable and collaborative, able to take direction and contribute to team priorities rather than needing to pursue a predetermined research agenda
• Are skilled at writing up and communicating your results, even when they're null or unexpected
• Are passionate about translating research insights into actionable recommendations for improving AI systems and informing policy

Logistics

Logistics Requirements: To participate in the Fellows program, you must have work authorization in the US, UK, or Canada and be located in that country during the program.

Workspace Locations: We have designated shared workspaces in London and Berkeley where fellows will work from and mentors will visit. We are also open to remote fellows in the UK, US, or Canada. We will ask you about your availability to work from Berkeley or London (full- or part-time) during the program.

Visa Sponsorship: We are not currently able to sponsor visas for fellows. To participate in the Fellows program, you need to have or independently obtain full-time work authorization in the UK, the US, or Canada.

Program Duration: The program runs for 4 months, full-time. If you can't commit to the full duration, please still apply and note your constraints in the application. We review these requests on a case-by-case basis.

Please note: We do not guarantee that we will make any full-time offers to fellows. However, strong performance during the program may indicate that a Fellow would be a good fit for full-time roles at Anthropic. In previous cohorts, 25-50% of fellows received a full-time offer, and we’ve supported many more to go on to do great work on AI safety and security at other organizations.

Applications and interviews are managed by Constellation, our recruiting partner. Clicking "Apply here" will take you to their portal, and updates will come from a Constellation address. Constellation also runs the Berkeley workspace and provides program support for fellows working on AI safety and security; fellows on capabilities-focused projects are supported directly by Anthropic. All applicants currently use the same application portal but we are working to separate applications for safety/security and capabilities focused projects in future rounds.

Apply here

The below are Anthropic's policies for full time roles. These do NOT apply to the Fellows Program.

Opportunity for Impact

Content is a critical growth lever at Taxbit. As a Content Marketing Manager, you will shape how the market understands who we are, the problems we solve, and why we win. Reporting to the Head of Content, Brand & Design, you will own the strategy and execution of high-impact content that builds credibility with enterprise buyers, drives qualified pipeline, and reinforces Taxbit’s position as the category leader in global tax information reporting for the digital economy. You will have a front row seat to the evolution of the global financial system as it becomes increasingly digital, translating complex regulatory and technical concepts into clear, compelling narratives that resonate with both executives and practitioners.

Key Responsibilities

• Optimize Taxbit’s content and brand credibility by producing compelling, search and LLM optimized content for our blogs, website, landing pages, social media channels, webinars, online profiles etc..
• Lead our interest driving content by collaborating with Taxbit SME’s, product marketing, design, sales, customers and industry experts
• Bring our social media engagement strategy to the next level by arming our executives and high profile internal SMEs with authentic content and stories that support our strategic narrative
• Monitor, track and document content performance and analyze performance to determine the impact on lead generation and revenue
• Produce content that attracts quality traffic to our blog and web pages including target prospects, partners, ecosystem influencers and customers
• Work hand in hand with our performance marketing and marketing operations team to measure the efficacy of our content program in increasing SEO and GEO rankings and web traffic 

Required Qualifications

• 5+ years in a content role at a high growth enterprise SaaS company
• Portfolio showcasing B2B content (samples required)
• Excellent written and verbal communication skills
• Experience working with highly technical content and subject matter experts to create brand content that sings
• Demonstrated success growing traffic and driving revenue through content marketing
• Hands on experience with website strategy & management, SEO & AEO, Social Media platforms (namely LinkedIn)
• Ability to think creatively and share brilliant ideas of how to make content of all types interesting and beautiful
• Impeccable organization and project management skills with the ability to work on multiple projects with many stakeholders
• Experience partnering with revenue and GTM leadership
• Self-directed, with the ability to prioritize and deliver in a high-growth environment
• Experience in fintech, compliance, or similarly complex and regulated industries strongly preferred

The base salary range for this role is $105,000-$145,000. Certain roles may be eligible for incentive compensation, equity, and benefits. Actual compensation will vary depending on various job-related factors, including, but not limited to location, experience, level, and job qualifications.

At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI platform so our customers can focus on the high-value challenges that are central to their own missions.

The Mosaic AI organization enables companies to develop AI models and systems using their own data, with technologies ranging from pre-training LLMs from scratch to augmented generation using the latest retrieval techniques. Mosaic AI does so by producing novel science and putting it into production. Mosaic AI is committed to the belief that a company’s AI models are just as valuable as any other core IP, and that high-quality AI models should be available to all.

Job Description

As a research engineer on the Scaling team, you will be responsible for keeping up with the latest developments in deep learning and advancing the scientific frontier by creating new techniques that go beyond the state of the art. You will work together on a collaborative team of researchers and engineers with diverse backgrounds and technical training. And most importantly, you will love our customers: our goal is to make our customers successful in applying state-of-the-art LLMs and AI systems, and we encode our scientific expertise into our products to make that possible.

The Impact you will have

As a research engineer on the Scaling Team at Databricks, you will: 

• Drive performance improvements through advanced optimization techniques including kernel fusion, mixed precision, memory layout optimization, tiling strategies, and tensorization for training-specific patterns
• Design, implement, and optimize high-performance GPU kernels for training workloads (e.g., attention mechanisms, custom layers, gradient computation, activation functions) targeting NVIDIA architectures
• Design and implement distributed training frameworks for large language models, including parallelism strategies (data, tensor, pipeline, ZeRO-based) and optimized communication patterns for gradient synchronization and collective operations
• Profile, debug, and optimize end-to-end training workflows to identify and resolve performance bottlenecks, applying memory optimization techniques like activation checkpointing, gradient sharding, and mixed precision training.

What We Look for

• BS/MS/PhD in Computer Science or related field with hands-on experience writing and tuning CUDA kernels for ML training applications, or hands-on experience in distributed training frameworks (PyTorch DDP, DeepSpeed, Megatron-LM, FSDP) 
• Strong understanding of NVIDIA GPU architecture (memory hierarchy, tensor cores, warp scheduling, SM occupancy) and proficiency with CUDA debugging/profiling tools (Nsight, NVProf)
• Deep understanding of parallelism techniques and memory optimization strategies for large-scale model training, with proven ability to debug and optimize distributed workloads
• Strong software engineering skills in Python and PyTorch, with experience supporting production training workflows and knowledge of LLM training dynamics including hyperparameter tuning and optimization strategies.

About the Role

You'll be Snorkel's primary technical voice in the open-source and research communities. The work spans three audiences: frontier AI research teams (post-training, RL environments, evals and benchmarks), enterprise ML and applied AI teams building specialized models on proprietary expertise, and the broader data-centric AI community.

You'll partner closely with our research, forward deployed research, and product teams to translate the methodology behind Snorkel's work into world-class technical content, open-source contributions, conference presence, and a thriving community of data-centric AI practitioners.

Success looks like: a strong Snorkel open-source presence, a steady cadence of high-signal technical writing and research artifacts, marquee presence at the conferences that matter (NeurIPS, ICML, ICLR, AI Engineer World's Fair), and an engaged community of researchers and practitioners who view Snorkel as the trusted authority on data development for modern AI.

Responsibilities

• Own Snorkel's external technical voice. Write methodology posts, technical deep-dives, and research-grade content on data development for frontier models. 
• Lead Snorkel's open-source presence. Define the GTM approach, ship code, review PRs, recruit contributors, and keep the libraries credible and current. Build OSS that demonstrates Snorkel's methodology in practice, including reproducible evals and benchmark artifacts.
• Advance the conversation on AI evaluation and benchmarking. Publish original work on how to measure agentic AI systems. Domain-specific evals, agent evals, LLM-as-judge calibration, contamination and saturation, and the connection between evals and post-training data.
• Drive conference and research community presence. Land talks, papers, and workshops at NeurIPS, ICML, ICLR, AI Engineer World's Fair, and the right practitioner venues. Build relationships with academic labs and AI research teams.
• Partner with the research team. Translate what's learned in research collaborations into externally shareable methodology, case studies, and tooling.
• Set the bar for technical credibility. Design evals and benchmarks, prototype RL environments, and write code worth using. Your authority comes from doing the work, not just talking about it.

Preferred Qualifications

• Experience. 6+ years in applied ML research, AI engineering, developer/research advocacy, or a research-intensive technical role with significant public output. Prior DevRel/advocate experience welcome but not required.
• Deep technical fluency in modern AI. Post-training techniques (RLHF, DPO, RLAIF), evaluation methodologies, RL environment design, training data pipelines, synthetic data generation, and at least one applied domain (coding agents, reasoning, multimodal, agents).
• Hands-on experience with AI evaluation and benchmarks. You've built and run real evals: public benchmarks (MMLU, GPQA, SWE-bench, HELM, BIG-bench, Arena-style head-to-heads), domain-specific custom evals, and LLM-as-judge pipelines with proper calibration. 
• You build with AI, not just about AI. A power user of frontier coding agents (Claude Code, Cursor, Codex, and the like) in your day-to-day workflow, and you've built non-trivial agentic systems yourself – multi-step, tool-using, with real evals and an opinion on what breaks.
• A real public body of work. Talks, papers, blog posts, podcasts, and/or OSS contributions you can point to. Quality and signal matter more than volume.
• Customer- and researcher-facing presence. Comfortable in a room with frontier-lab research leads or a F500 ML team; can read the room and hold technical credibility on either side.
• Self-directed and comfortable with ambiguity. You ship without being asked, set your own quality bar, and enjoy moving at the pace of frontier AI.

Bonus: Advanced degree or sustained research output in ML/AI; prior experience at an AI lab, OSS-first AI company, or a research-driven technical org; conference program-committee or organizing experience; published or maintained a public benchmark; relationships in the post-training, evals, or RL-environments communities.

About the role:

As a Product Support Specialist, you’ll be at the front lines of safely delivering AI to the world by responding to, investigating, and tracking user needs in your day to day. Additionally, you’ll help us identify – and close – gaps in our team’s technical knowledge, provide high-touch support to strategic customers, and demonstrate deep care for how we systematically support customers at scale. 

Responsibilities:

• Become an expert in all Anthropic products
• Respond to user support cases with a variety of complexity, from questions for individuals to complex API debugging for large businesses 
• Clearly and empathetically communicate with a wide range of user personas, context-switching between guiding executives in a high-touch model to assisting consumer users in a rapid pace
• Manage on-call tasks for high-urgency user issues with extreme ownership
• Prioritize critically and comfortably adapt to an ever-evolving product landscape
• Operate in ambiguity, making informed decisions even in never-before-seen situations
• Partner with engineers, teammates, and other internal stakeholders to diagnose and resolve user issues, both individually and at scale
• Suggest and drive improvements to increase user satisfaction through support processes as well as own initiatives that increase efficiency and drive down contact rates
• Uplevel our team’s technical knowledge by scoping gaps, working with cross-functional partners to deeply understand relevant nuances, and building resources that grow with our products

You may be a good fit if you:

• 3 - 5 years of relevant experience in technical product support in a high growth tech company, including API debugging, preferably in a second tier, escalated, or priority support team
• Are familiar with APIs and technical SaaS products and can deeply understand technical docs with ease
• Have demonstrated an ability to thrive in fast-paced, reactive situations while meeting core support metrics targets (e.g. CSAT, SLA, etc.)
• Possess strong user empathy and are expert in the lifecycle of a support case; you can read between the lines of a user’s question, put yourself in their shoes, and get at the heart of their needs for a speedy, satisfying resolution
• Have crisp but kind written communication skills and a deep care for the details
• Enjoy helping others learn about new features and complex concepts
• Experience troubleshooting SSO, SAML, and OAuth authentication flows
• Are persistent and curious; you delight in the hunt of tracking down a bug or issue, and are energized by fixing this for all similar users going forward
• Have experience contributing to the foundations of a support team – this is essential, highly valuable, but often unglamorous work
• Are proficient at working in a technical environment and are interested in Anthropic’s products
• Possess a deep sense of ownership, and are excited to help us build our team!

Strong candidates may also have:

While not required, we're particularly excited about candidates with one or more of these specializations:

• Comfort with command line interfaces and basic scripting (Bash, Python, JavaScript)
• Understanding of LLM capabilities, practical applications, and current limitations
• Familiarity with enterprise networking concepts and IT infrastructure
• Familiarity with Git workflows and version control concepts
• SQL proficiency for querying logs and investigating issues
• Experience supporting government or public sector customers, including familiarity with compliance requirements and security frameworks
• Background in team lead roles or managing contract/vendor support teams

We're hiring across a range of experience levels to build depth in both technical capabilities and enterprise support.

Okta’s Business Technology organization builds secure and intelligent internal platforms that power our global workforce. Our AI & Automation team is delivering next-generation tools and experiences by integrating GenAI and intelligent automation into workflows across IT, HR, Finance, Sales, Marketing and Customer Support.

We focus on real-world applications: virtual agents, AI copilots, internal RAG services, and AI-augmented self-service portals — all with scale, governance, and user experience in mind.

The Opportunity

As a Senior Software Engineer, Applied AI, you’ll play a key role in building user-facing and backend systems that leverage GenAI to improve internal experiences and operations. This role requires strong full-stack engineering skills, with an emphasis on both AI integration and building intuitive, performant UIs that make AI accessible and useful to our internal customers.

You’ll work closely with software engineers, product managers, and designers to build secure, intelligent tools for employees across Okta.

What You’ll Do

• Design and build end-to-end GenAI-powered applications, including web-based UIs, API services, and backend orchestration.

• Implement and integrate LLM-based experiences using frameworks like LangChain, LlamaIndex, and tools like OpenAI, Claude, or Gemini.

• Define, implement, and champion operational excellence standards (SLOs, observability, incident response frameworks) for all services deployed.

• Develop responsive, accessible, and modern frontend interfaces using frameworks like React or Vue — with a focus on usability, performance, and trust in AI outputs.

• Build and maintain a library of reusable frontend components and hooks that allow other business delivery teams to easily "drop in" GenAI capabilities into their own applications.

• Build and maintain retrieval-augmented generation (RAG) pipelines with vector search and embedding strategies (e.g., Pinecone, FAISS, Qdrant).

• Collaborate with designers and product managers to rapidly iterate on UX patterns for AI-powered experiences (e.g., prompt inputs, citations, summaries).

• Ensure security, privacy, observability, and test coverage across the full stack.

• Contribute to architecture decisions, engineering standards, and best practices for AI/automation systems.

• Partner with platform and infrastructure teams to ensure services scale reliably across the org.

What You’ll Bring

• 5–8 years of software engineering experience with full-stack development, including 2+ years of building AI/ML-driven applications.

• Strong Python development skills and 5+ years experience building cloud-based services using AWS, Docker, and RESTful APIs.

• 2+ years of experience in frontend technologies like React, TypeScript, or Vue, and comfort working on UI/UX for internal tools or enterprise applications.

• Hands-on experience with LLM integration, RAG pipelines, prompt engineering, or orchestration frameworks like LangChain or LlamaIndex.

• Strong background in distributed systems, APIs, microservices, container orchestration (ECS/EKS), and cloud platforms (AWS/GCP/Azure).

• Familiarity with secure coding, authentication/authorization, and internal data governance best practices.

• Ability to collaborate across engineering, design, and product teams — with a strong sense of user empathy and technical ownership.

• Bonus: Exposure to design systems, AI evaluation tooling, or real-time application performance monitoring.

Why Join Okta

• Make AI Real: Design and build AI-powered apps used daily by Okta employees.

• Full-Stack Challenge: Tackle end-to-end problems — from LLM orchestration to intuitive UIs.

• Trusted Innovation: Join a team committed to security, ethics, and technical excellence in AI.

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The Role

As an Applied AI Marketing Engineer, you will be a core, hands-on builder within the new Marketing AI Spoke team. You will function as the primary product owner and technical implementer for a specific portfolio of AI agents, workflows, and low-code/no-code applications. This role requires a blend of marketing acumen, technical aptitude, and problem-solving skills to translate complex business challenges into tangible, deployed, AI-driven solutions.

You will be responsible for the full engineering lifecycle—defining, developing, testing, and deploying high-impact initiatives that directly improve our marketing productivity, operational efficiency, and buyer experiences.

Responsibilities

• Marketing AI Solution Development: Patterning with TDI leveraging company-wide approved platform. Design, build, and maintain the underlying infrastructure and services required to run scalable AI applications for the Marketing organization. This includes connecting data sources, building APIs, developing front-end user interfaces (UI/UX), and engineering the backend logic.
• AI Agent & Workflow Engineering: Architect, code, test, and deploy AI agents and low-code/no-code workflows that solve critical marketing challenges. Ensure solutions are robust, secure, and seamlessly integrated into the existing AI stack (e.g., CRM, MAP, CMS).
• Agentic Strategy & Architectural Design: Act as the technical leader for your assigned portfolio, defining the architectural blueprints for new AI enabled workflows. Evaluate and recommend the appropriate technical tooling (e.g., cloud services, databases, low-code platforms) to maximize performance and minimize operational costs.
• Data and Prompt Engineering: Partner with data science and marketing ops teams to ensure data pipelines support AI application needs (RAG, fine-tuning). Design and iterate on effective prompts and input-output schemas to optimize the performance and reliability of large language model (LLM) agents.
• Value Measurement & System Optimization: Implement performance tracking directly into deployed platforms (instrumentation). Use technical metrics (latency, uptime, error rates) and business metrics (ROI, time saved) to justify system improvements and guide the marketing AI roadmap. 

What You'll Bring

• A Bias for Action and Iteration: Demonstrated passion for a test-and-learn philosophy, quickly prototyping and validating solutions to drive continuous improvement.
• AI-First Technology Mindset: Deep curiosity and commitment to leveraging AI and machine learning as foundational elements for building next-generation marketing tools and operational workflows.
• Marketing Domain Curiosity: A strong interest in marketing dynamics, customer behavior, and business outcomes, translating technical capabilities into tangible marketing value.
• Preferred Experience (A Strong Plus): Prior background in marketing operations, strategy, or experience working on tools/platforms utilized by large-scale marketing organizations.

Why You'll Love This Role

• Become the Architect of Change: You won't be maintaining existing systems; you will be building a new, high-impact function from the ground up. This is a chance for true architectural ownership over the next generation of our marketing operating model.
• Tangible and Immediate Impact: Your work on groundbreaking AI projects will have a direct, measurable impact on our business performance, customer experience, and efficiency. You will see your innovations adopted by hundreds of marketers and contribute to trillions in potential value.
• High-Visibility, Strategic Ownership: This role offers executive-level visibility as you directly shape the future of marketing strategy at Okta, moving the function from manual repetition to hyper-efficient, data-driven automation.

#LI-Hybrid
PID: P24412_3380938

Okta- Solutions Engineer- SLED

The Solutions Engineer Team

We believe Solutions Engineers at Okta are involved in all stages of the customer’s digital transformation.  Solutions Engineers are experienced using presentations, email, phone and social media to connect with customers virtually and in-person. We are looking for great teammates who can build and deliver sales presentations and customized product demonstrations to help educate Okta’s Customers (everyone from developers to product managers to C-level executives) on best practices during their cloud security technology journey. We believe Okta’s Solutions Engineers empathize with Customers and quickly discern their true technical needs by asking detailed, clarifying questions while presenting solutions that specifically address those needs. Okta Solution Engineers have the rare combination of technical acumen and business insight; in a career where you can utilize both. As a Solutions Engineer at Okta, you will further develop each of these skills by advising a diverse set of customers on the value they will gain by using Okta’s Identity Platform.

The Solutions Engineer Opportunity

Reporting to the Senior Manager of Solutions Engineers, the Solutions Engineer is a functional business consultant,  with a passion for technology and the advanced ability to develop, position and demonstrate product-specific solutions during sales cycles, while achieving quarterly and annual sales goals for an assigned territory.

What you’ll be doing 

• Work alongside the sales team as the technical and domain expert of a customer-facing sales team to help Customers understand the value of Okta’s solutions
• Understand customer challenges and business issues and provide product demonstrations to align our solutions with customer needs
• Answer product feature and technical questions from customers, partners and Okta colleagues
• Plan and deliver Proof Of Concepts for customers who have more complex use cases, collaborating with other Okta engineering teams as needed
• Provide feedback to product management about product enhancements that can address customer needs and provide additional value
• Share and learn best practices and re-usable assets with other Solutions Engineers to enhance the quality and efficiency of the team
• Stay current on competitive analysis and market differentiation
• Support marketing events including executive briefings, conferences, user groups, and trade shows
• At times, be asked to learn and lead your team as a subject matter expert (SME) with various product solutions and/or competitive knowledge

What you’ll bring to the role

• 3-5+ years pre-sales engineering experience.
• A passion to serve the Customer, demonstrated in a customer-facing role, such as consulting or support, but ideally in a pre-sales capacity.
• An ability to quickly communicate complex ideas around a technical topic, ideally on the fly, using a whiteboard.
• Deployed apps in cloud platforms: AWS, Azure, GCP, Vercel, etc.
• Experience with at least one standard network security protocol. (eg. OAuth, OAuth2, SAML, LDAP)
• Experience working with REST APIs, API Gateways, and SDKs
• Hands-on experience in one or more of the following areas: web (JavaScript, HTML, frontend frameworks) development, mobile (iOS, Android) development, backend (Java, C#, Node.js, Python, PHP, Ruby) development, IP-based real-time communications
• An understanding of core security concerns within a typical application. (password hashing, SSL/TLS, encryption at rest, XSS, XSRF)
• Exceptional communicator.
• Confident dispensing knowledge to a highly skilled and experienced audience, presenting to large rooms filled with experts in the field
• Territory management skills, including pipeline building and working with Sales counterparts to guide execution excellence
• Typically 25% travel.
• Bachelor's degree in Engineering, Computer Science, MIS or a comparable field is preferred.

You might also have (not mandatory):

• Hands-on experience with Generative AI or LLM technology such as LangChain, GenKit, LlamaIndex, etc.
• Experience integrating with microservices, data lakes, or customer data platforms.
• Developed ReBAC or Fine Grain Authorization models
• Diagramming experience for user journey flows, complex architecture diagrams, etc.

#LI-San Francisco

#LI-RZ

P24424_3330263

The Global Pricing Operations Team

The Pricing Operations team works in a cross-functional, fast-paced, and dynamic environment with many moving pieces and shifting priorities. The team partners with Pricing Strategy Managers, Product Managers,Technology, Data & Intelligence,  and various GTM teams to ensure that Okta's business is ready to operate with the launch of new product pricing and pricing strategies. 

The Pricing Operations Manager Opportunity

Okta is seeking a Pricing Operations Manager to drive initiatives that transform Okta's pricing strategy into successful go-to-market execution. A successful person in this role will be a strong collaborator, intensely curious, and supremely organized. They are known for connecting the dots, simplifying complexities, communicating clearly and proactively, and driving highly collaborative efforts to completion, even when the path forward isn't perfectly defined. 

For pricing launches, you will be the point person to evaluate the operational impact of pricing initiatives across several Okta teams and partner with those teams to build and execute an operational launch readiness plan. You will work closely with our Technology, Data & Intelligence leads for Salesforce and CPQ to prepare and maintain Okta's SKU catalog and support the creation and maintenance of pricing enablement materials for Sales and GTM teams.

As Okta rapidly launches new innovations and expands into new markets, this role is critical to our success.

What you’ll be doing

• Drive cross-functional initiatives to transform pricing strategy into successful go-to-market execution
• Collaborate closely with several functions across the company — including Pricing Strategy, Product, Product Marketing, Legal, Finance, GTM, and Technology, Data & Intelligence — to evaluate the operational impact of pricing initiatives, develop operational readiness plans, and execute launches
• Navigate ambiguity and fast-moving strategy decisions with confidence, helping the team align quickly and move forward effectively
• Continuously assess and re-prioritize workstreams as business needs evolve, maintaining clarity and momentum across multiple concurrent initiatives
• Drive strategic projects to optimize and automate pricing processes, standards, and engagement frameworks
• Develop business requirements for Technology, Data & Intelligence to build new SKUs in Okta's business systems to support quoting, invoicing, revenue recognition, reporting, and improved transaction processes for Okta's sales teams
• Proactively synthesize and communicate status updates, risks, and blockers to leaders and cross-functional stakeholders for pricing launches — not just when asked, but as a consistent habit
• Gather GTM team feedback on the quality and effectiveness of pricing enablement and training content; develop new and optimize existing pricing enablement and training content for the sales team
• Serve as SME on pricing, product configuration, and go-to-market processes
• Actively contribute to team culture by seeking and incorporating feedback, sharing learnings, and helping raise the bar for how the Pricing Operations function operates

What you'll bring to the role

• Bachelor's degree in Computer Science, Finance, Marketing, Business, or equivalent experience
• Minimum of 8 years of experience in a business operations or program management role, ideally at a SaaS or enterprise software company; preferably 2+ years in a pricing operations role
• Demonstrated ability to thrive in a fast-paced, high-pressure environment where priorities shift and decisions need to be made quickly with incomplete information
• A track record of strong, proactive communication: keeping stakeholders informed, surfacing issues early, and driving alignment across teams with transparency and clarity
• A learner mentality with an owner mindset: someone who actively seeks feedback, iterates on their approach, and views challenges as opportunities for growth
• Action-oriented with a strong bias toward outcomes: able to solve problems and deliver results in short timeframes
• Demonstrated leadership experience driving complex, cross-functional execution, with a collaborative approach that builds trust across teams and levels
• Exceptional verbal and written communication skills across all levels of an organization
• Proficiency with Salesforce and CPQ, with direct experience supporting or executing system builds (including creating and managing quotable SKUs, custom fields, validation rules, and alert rules to support the quote to cash process), as well as working proficiency across Jira, Google Workspace, and AI/LLM tools to drive operational efficiency and support day-to-day execution.
• Experience working within or closely alongside sales-adjacent teams such as Deal Desk, Deal Strategy, GTM Strategy & Operations, or similar functions, with a solid understanding of how sales teams operate, what they need to close deals, and how pricing and operational decisions affect their work. 

What Will Make You Stand Out

• Experience operating in a high-growth or rapidly evolving company environment where structure and process are still being built
• A history of building strong cross-functional relationships and earning trust as a reliable, communicative partner, even when delivering difficult updates
• Comfort with ambiguity and change, paired with the discipline to bring order and clarity to complex situations
• Evidence of continuous improvement mindset: you regularly reflect on what's working, ask for feedback, and find ways to do things better

This role demands both strategic thinking and operational excellence, and the resilience and adaptability to succeed when both are needed at the same time. If you do your best work in a collaborative, fast-moving environment and take pride in being the person who keeps things moving forward, we'd love to hear from you.

What you can look forward to as an Okta employee!

• Amazing Benefits
• Making Social Impact
• Fostering Diversity, Equity, Inclusion and Belonging at Okta 

Okta cultivates a dynamic work environment, providing the best tools, technology and benefits to empower our employees to work productively in a setting that best and uniquely suits their needs. Each organization is unique in the degree of flexibility and mobility in which they work so that all employees are enabled to be their most creative and successful versions of themselves, regardless of where they live. Find your place at Okta today! https://www.okta.com/company/careers/.

Okta is an Equal Opportunity Employer/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws. If reasonable accommodation is needed to participate in the job application or interview process, please use this Form to request an accommodation.

Okta is committed to complying with applicable data privacy and security laws and regulations. For more information, please see our Privacy Policy at https://www.okta.com/privacy-policy/. 

ir needs. Each organization is unique in the degree of flexibility and mobility in which they work so that all employees are enabled to be their most creative and successful versions of themselves, regardless of where they live. Find your place at Okta today! https://www.okta.com/company/careers/.

Okta is an Equal Opportunity Employer/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws. If reasonable accommodation is needed to participate in the job application or interview process, please use this Form to request an accommodation.

Okta is committed to complying with applicable data privacy and security laws and regulations. For more information, please see our Privacy Policy at https://www.okta.com/privacy-policy/.

#LI-HM2

#LI-Hybrid

P22030_3425948

The Auth0 Team

Auth0 is an easy-to-implement authentication and authorization platform designed by developers for developers.  We make access to applications safe, secure, and seamless for the more than 100 million daily logins around the world. Our modern approach to identity enables this Tier-Ø global service to deliver convenience, privacy, and security so customers can focus on innovation.

This team focuses on providing tenant-level protections to our customers, at scale. From bot detection to brute-force to suspicious IP throttling and beyond, this team often provides the first line of defense for Auth0 customers.

The Staff Software Engineer 

At Okta, we’re building the next generation of authentication for the GenAI era. 

We’re looking for a Staff Software Engineer to join the AI DevEx team at Auth0. This role is pivotal in extending and complementing our Auth for GenAI offering by building the infrastructure, tooling, and developer experiences that empower both human developers and AI agents to build secure, intelligent applications.

Auth0 Emerging Tech is the Engineering organization where we take care of the hottest technology out there: we ship fast, we don't break things. We are a dynamic and collaborative distributed and diverse team. We value ownership, learning and innovation.  

This is an ideal role for an engineer who enjoys building for other engineers, working across stacks, and shaping the future of AI enablement in production systems. You'll collaborate across engineering, product, and security teams to drive meaningful improvements in developer tooling, agent authentication, orchestration frameworks, and real-world demos.

What you will be doing:

• Design and Build Developer Tooling that helps developers secure and manage infrastructure like MCP servers
• Build Demo Applications that showcase secure, identity-powered AI use cases in real-world environments
• Contribute to Open Source Projects, both within Auth0 and across the broader AI + identity ecosystem
• Write and Maintain High-Quality Documentation including API references, quickstarts, and best practices for both developers and AI-native tooling (e.g., llm.txt)
• Drive Integration with Emerging AI Frameworks by creating adapters, utilities, and interfaces for agent runtimes and orchestration layers
• Collaborate with Design, Product, and Security teams to align on developer needs, roadmap direction, and compliance requirements
• Mentor and Support Other Engineers, setting strong examples in code quality, testing practices, and architectural thinking
• Influence Engineering Standards by leading design discussions and contributing to team-wide architectural decisions
• Ensure Resilience and Security of systems involved in agent-to-agent or model-to-service communication

You Might Be a Good Fit If You

• Experience in software engineering with a proven track record in building tools, frameworks, or platforms for other developers
• Proficiency in JavaScript/TypeScript, Golang and/or Python, and the ability to move fluidly between front-end and back-end contexts
• Experience working with LLM APIs, agent runtimes, orchestration layers, or prompt pipelines
• Familiarity with authentication and authorization systems, especially standards like OAuth2, OIDC, and JWT
• Demonstrated experience leading architecture and design efforts for scalable, production-grade systems
• Comfort contributing to and maintaining open source projects and engaging with developer communities
• A passion for documentation as part of the developer experience—not just writing code, but making it understandable and usable
• Ability to thrive in highly collaborative environments with cross-functional stakeholders

Technologies You May Work With

• Languages: JavaScript, TypeScript, Python
• Frameworks: React, Next.js, FastAPI
• AI Ecosystem: Model APIs, orchestration runtimes, prompt management systems, agent toolkits
• Auth0 Stack: Token Vault, Async Authorization, Fine-Grained Authorization (FGA)

#LI-Hybrid

P23578_3268067

The Global Data & Insights Team

Okta's Enterprise Data & Insights team powers the data infrastructure that drives decision-making across the company by building reliable pipelines, scalable data platforms, and production-grade data products. We partner closely with internal Data and Insights Analysts as well as external Okta Product teams to unlock business value through robust data architecture, efficient data movement, and the engineering foundations that make data trustworthy at scale.    

The Senior Analytics Engineer, Marketing Opportunity

We are seeking a Senior Analytics Engineer to serve as the technical architect of our marketing data engine. You will own our marketing attribution logic and end-to-end funnel performance data, evolving our current processes into an enterprise-grade ecosystem. Your mission is to uncover the high-fidelity signals that drive new customer acquisition and maximize expansion within our existing base. You’ll tackle a sophisticated roadmap of advanced analytics, transforming raw touchpoints into a trusted, scalable framework for growth.

This role sits at the intersection of business context and technical execution. You will design scalable data models, define consistent business logic, and help establish a strong semantic foundation that enables both human analytics and machine-driven intelligence.

You will partner closely with Marketing stakeholders, Data Analysts, Data Scientists, and Data Engineers to ensure data is accurate, consistent, and easy to consume; whether through dashboards, self-service exploration, or AI-powered workflows.

What you’ll be doing

Data Modeling & Semantics

• Design, build, and maintain scalable data models using dbt and Snowflake
• Define and standardize core Marketing metrics (e.g., pipeline, campaign performance, attribution, conversion rates)
• Establish consistent modeling patterns, naming conventions, and semantic clarity across datasets
• Contribute to a shared semantic layer that enables consistent reporting across channels and tools

AI-Ready Data & Snowflake Ecosystem

• Prepare high-quality, well-governed datasets for use with Snowflake Cortex and Snowflake Intelligence
• Enable data foundations that support LLM-powered use cases such as campaign insights, segmentation, and performance optimization
• Ensure data is context-rich, well-documented, and aligned with business meaning to improve AI accuracy and usability

Data Quality, Governance & Trust

• Implement robust testing, validation, and documentation practices in dbt
• Ensure consistency across dashboards and marketing tools through shared definitions and reusable models
• Apply data governance best practices, including access controls, lineage, and auditability
• Partner across teams to establish clear ownership of marketing data assets and definitions

Collaboration & Delivery

• Partner with Marketing, Customer First, and Analytics teams to translate business needs into scalable data solutions
• Support self-service analytics by building intuitive, reusable datasets across channels (e.g., digital, lifecycle, events)
• Contribute to scalable data workflows that balance immediate campaign needs with long-term maintainability
• Work within an agile environment, contributing to planning, prioritization, and continuous improvement

AI and Data Mindset

• Demonstrate an AI-first mindset, thinking beyond data models and dashboards to how data can power intelligent systems and decision-making
• Understand the importance of well-modeled, well-documented, and semantically clear data for AI and LLM-based use cases
• A level of comfort leveraging AI-assisted workflows to improve productivity, code quality, and consistency
• Curiosity for emerging capabilities in platforms like Snowflake Cortex and Snowflake Intelligence, and how they can be applied to Marketing analytics

What you’ll bring to the role

• 5–8+ years of experience in Analytics Engineering, Data Engineering, or similar roles
• Strong SQL skills and experience building analytics-ready data models
• Mentorship & Engineering Excellence: Mentorship, raising the technical bar, establishing organization-wide standards for dbt/SQL quality and CI/CD
• Hands-on experience with dbt and Snowflake or other ETL, Modeling and database platforms
• Solid understanding of data modeling principles, including dimensional modeling and semantic design
• Experience working with Marketing data (e.g., campaign data, web analytics, CRM, attribution models)
• Familiarity with tools such as Salesforce, Marketo, Google Analytics, or similar platforms
• Experience with data quality, testing, and documentation best practices
• Exposure to Python, R, or data processing frameworks (e.g., PySpark) is a plus
• Experience with BI tools such as Tableau or Looker
• Strong communication skills and ability to work across technical and business teams

What you can look forward to as an Okta employee!

• Amazing Benefits
• Making Social Impact
• Fostering Diversity, Equity, Inclusion and Belonging at Okta 
• Okta cultivates a dynamic work environment, providing the best tools, technology and benefits to empower our employees to work productively in a setting that best and uniquely suits their needs. Each organization is unique in the degree of flexibility and mobility in which they work so that all employees are enabled to be their most creative and successful versions of themselves, regardless of where they live. Find your place at Okta today! https://www.okta.com/company/careers/.

Okta is an Equal Opportunity Employer/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws. If reasonable accommodation is needed to participate in the job application or interview process, please use this Form to request an accommodation.

Okta is committed to complying with applicable data privacy and security laws and regulations. For more information, please see our Privacy Policy at https://www.okta.com/privacy-policy/. 

Each organization is unique in the degree of flexibility and mobility in which they work so that all employees are enabled to be their most creative and successful versions of themselves, regardless of where they live. Find your place at Okta today! https://www.okta.com/company/careers/.

Okta is an Equal Opportunity Employer/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws. If reasonable accommodation is needed to participate in the job application or interview process, please use this Form to request an accommodation.

Okta is committed to complying with applicable data privacy and security laws and regulations. For more information, please see our Privacy Policy at https://www.okta.com/privacy-policy/.

#LI-HM2

#LI-Hybrid

P24712_3413650

P24715_3413656

The Senior Solutions Engineer Opportunity

Reporting to the Senior Manager of Solutions Engineers, the Sr Solutions Engineer (Corporate New Business) is a functional business consultant,  with a passion for technology and the advanced ability to develop, position and demonstrate product-specific solutions during sales cycles, while achieving quarterly and annual sales goals for an assigned territory. A background in software development and experience with developer-centric identity platforms (such as Auth0) can be particularly impactful, enabling you to deeply understand and articulate the value of Auth0 by Okta from a technical implementer's perspective.

What you’ll be doing 

• Work alongside the Corporate/New Business (employee size 300-1249) sales team as the technical and domain expert of a customer-facing sales team to help Customers understand the value of Okta’s solutions
• Understand customer challenges and business issues especially those faced by development and product teams - and provide product demonstrations to align our solutions with customer needs.
• Answer product features and technical questions from customers, partners and Okta colleagues.
• Plan and deliver Proof Of Concepts for customers who have more complex use cases, collaborating with other Okta engineering teams as needed. This will include scripting and coding to showcase Auth0’s capabilities.
• Provide feedback to product management about product enhancements that can address customer needs and provide additional value.
• Share and learn best practices and re-usable assets with other Solutions Engineers to enhance the quality and efficiency of the team.
• Stay current on competitive analysis and market differentiation.
• Support marketing events including executive briefings, conferences, user groups, and trade shows.
• At times, be asked to learn and lead your team as a subject matter expert (SME) with various product solutions and/or competitive knowledge.

What you’ll bring to the role

• 8+ years pre-sales engineering experience.
• A passion to serve the Customer, demonstrated in a customer-facing role, such as consulting or support, but ideally in a pre-sales capacity.
• An ability to quickly communicate complex ideas around a technical topic, ideally on the fly, using a whiteboard.
• Deployed apps in cloud platforms: AWS, Azure, GCP, Vercel, etc.
• Experience with at least one standard network security protocol. (eg. OAuth, OAuth2, SAML, LDAP)
• Experience working with REST APIs, API Gateways, and SDKs
• Hands-on experience in one or more of the following areas: web (JavaScript, HTML, frontend frameworks) development, mobile (iOS, Android) development, backend (Java, C#, Node.js, Python, PHP, Ruby) development, IP-based real-time communications.
• Leverage your software development background to effectively communicate with technical audiences, including developers, architects, and DevOps engineers, translating their requirements into robust solutions.
• An understanding of core security concerns within a typical application. (password hashing, SSL/TLS, encryption at rest, XSS, XSRF)
• Exceptional communicator.
• Confident dispensing knowledge to a highly skilled and experienced audience, presenting to large rooms filled with experts in the field
• Territory management skills, including pipeline building and working with Sales counterparts to guide execution excellence.
• Typically 25% travel.
• Bachelor's degree in Engineering, Computer Science, MIS or a comparable field is preferred.

You might also have (not mandatory):

• Hands-on experience with Generative AI or LLM technology such as LangChain, GenKit, LlamaIndex, etc.
• Experience integrating with microservices, data lakes, or customer data platforms.
• Developed ReBAC or Fine Grain Authorization models.
• Diagramming experience for user journey flows, complex architecture diagrams, etc.

Preferred Experience (bonus points):

• Trusted Advisor in your sales region (Area Sales Director and Area Vice President)
• Experience leading highly strategic technical sales plays, targeting new account acquisitions, or transferrable experiences preferred.
• Creation of reusable artifacts to be adopted by the presales and/or sales community.
• Publication of thought leadership documentation externally annually.
• Technical leader among peers and a mentor to help grow others in the segment.

LI#Remote

LI#CM

P7161_3396398

Okta’s Business Technology organization builds secure and intelligent internal platforms that power our global workforce. Our AI & Automation team is delivering next-generation tools and experiences by integrating GenAI and intelligent automation into workflows across IT, HR, Finance, Sales, Marketing and Customer Support.

We focus on real-world applications: virtual agents, AI copilots, internal RAG services, and AI-augmented self-service portals — all with scale, governance, and user experience in mind.

The Opportunity

As a Senior Software Engineer, Applied AI, you’ll play a key role in building user-facing and backend systems that leverage GenAI to improve internal experiences and operations. This role requires strong full-stack engineering skills, with an emphasis on both AI integration and building intuitive, performant UIs that make AI accessible and useful to our internal customers.

You’ll work closely with software engineers, product managers, and designers to build secure, intelligent tools for employees across Okta.

What You’ll Do

• Design and build end-to-end GenAI-powered applications, including web-based UIs, API services, and backend orchestration.

• Implement and integrate LLM-based experiences using frameworks like LangChain, LlamaIndex, and tools like OpenAI, Claude, or Gemini.

• Define, implement, and champion operational excellence standards (SLOs, observability, incident response frameworks) for all services deployed.

• Develop responsive, accessible, and modern frontend interfaces using frameworks like React or Vue — with a focus on usability, performance, and trust in AI outputs.

• Build and maintain a library of reusable frontend components and hooks that allow other business delivery teams to easily "drop in" GenAI capabilities into their own applications.

• Build and maintain retrieval-augmented generation (RAG) pipelines with vector search and embedding strategies (e.g., Pinecone, FAISS, Qdrant).

• Collaborate with designers and product managers to rapidly iterate on UX patterns for AI-powered experiences (e.g., prompt inputs, citations, summaries).

• Ensure security, privacy, observability, and test coverage across the full stack.

• Contribute to architecture decisions, engineering standards, and best practices for AI/automation systems.

• Partner with platform and infrastructure teams to ensure services scale reliably across the org.

What You’ll Bring

• 5–8 years of software engineering experience with full-stack development, including 2+ years of building AI/ML-driven applications.

• Strong Python development skills and 5+ years experience building cloud-based services using AWS, Docker, and RESTful APIs.

• 2+ years of experience in frontend technologies like React, TypeScript, or Vue, and comfort working on UI/UX for internal tools or enterprise applications.

• Hands-on experience with LLM integration, RAG pipelines, prompt engineering, or orchestration frameworks like LangChain or LlamaIndex.

• Strong background in distributed systems, APIs, microservices, container orchestration (ECS/EKS), and cloud platforms (AWS/GCP/Azure).

• Familiarity with secure coding, authentication/authorization, and internal data governance best practices.

• Ability to collaborate across engineering, design, and product teams — with a strong sense of user empathy and technical ownership.

• Bonus: Exposure to design systems, AI evaluation tooling, or real-time application performance monitoring.

Why Join Okta

• Make AI Real: Design and build AI-powered apps used daily by Okta employees.

• Full-Stack Challenge: Tackle end-to-end problems — from LLM orchestration to intuitive UIs.

• Trusted Innovation: Join a team committed to security, ethics, and technical excellence in AI.

#LI-MK1

#LI-hybrid

P24739_3355024

Okta’s Business Technology organization builds secure and intelligent internal platforms that power our global workforce. Our AI & Automation team is delivering next-generation tools and experiences by integrating GenAI and intelligent automation into workflows across IT, HR, Finance, Sales, Marketing and Customer Support.

We focus on real-world applications: virtual agents, AI copilots, internal RAG services, and AI-augmented self-service portals — all with scale, governance, and user experience in mind.

The Opportunity

As a Senior Software Engineer, Applied AI, you’ll play a key role in building user-facing and backend systems that leverage GenAI to improve internal experiences and operations. This role requires strong full-stack engineering skills, with an emphasis on both AI integration and building intuitive, performant UIs that make AI accessible and useful to our internal customers.

You’ll work closely with software engineers, product managers, and designers to build secure, intelligent tools for employees across Okta.

What You’ll Do

• Design and build end-to-end GenAI-powered applications, including web-based UIs, API services, and backend orchestration.

• Implement and integrate LLM-based experiences using frameworks like LangChain, LlamaIndex, and tools like OpenAI, Claude, or Gemini.

• Define, implement, and champion operational excellence standards (SLOs, observability, incident response frameworks) for all services deployed.

• Develop responsive, accessible, and modern frontend interfaces using frameworks like React or Vue — with a focus on usability, performance, and trust in AI outputs.

• Build and maintain a library of reusable frontend components and hooks that allow other business delivery teams to easily "drop in" GenAI capabilities into their own applications.

• Build and maintain retrieval-augmented generation (RAG) pipelines with vector search and embedding strategies (e.g., Pinecone, FAISS, Qdrant).

• Collaborate with designers and product managers to rapidly iterate on UX patterns for AI-powered experiences (e.g., prompt inputs, citations, summaries).

• Ensure security, privacy, observability, and test coverage across the full stack.

• Contribute to architecture decisions, engineering standards, and best practices for AI/automation systems.

• Partner with platform and infrastructure teams to ensure services scale reliably across the org.

What You’ll Bring

• 5–8 years of software engineering experience with full-stack development, including 2+ years of building AI/ML-driven applications.

• Strong Python development skills and 5+ years experience building cloud-based services using AWS, Docker, and RESTful APIs.

• 2+ years of experience in frontend technologies like React, TypeScript, or Vue, and comfort working on UI/UX for internal tools or enterprise applications.

• Hands-on experience with LLM integration, RAG pipelines, prompt engineering, or orchestration frameworks like LangChain or LlamaIndex.

• Strong background in distributed systems, APIs, microservices, container orchestration (ECS/EKS), and cloud platforms (AWS/GCP/Azure).

• Familiarity with secure coding, authentication/authorization, and internal data governance best practices.

• Ability to collaborate across engineering, design, and product teams — with a strong sense of user empathy and technical ownership.

• Bonus: Exposure to design systems, AI evaluation tooling, or real-time application performance monitoring.

Why Join Okta

• Make AI Real: Design and build AI-powered apps used daily by Okta employees.

• Full-Stack Challenge: Tackle end-to-end problems — from LLM orchestration to intuitive UIs.

• Trusted Innovation: Join a team committed to security, ethics, and technical excellence in AI.

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P24739_3355024

AI Engineer
Location: San Francisco, CA, in-office
Compensation: 150,000 – $210,000
Company: Cargomatic, Inc.

Disruptive, groundbreaking, transformative company is changing an industry

Join a rapidly growing company disrupting the trucking industry! Cargomatic is the #1 technology platform and digital marketplace for powering world-class, local trucking. Take a look around you. Literally everything humans build, grow, or sell has spent time on a truck. Local trucking is the lifeblood of every regional economy, and yet this $82 billion industry still relies heavily on phone calls and fax machines. Cargomatic is transforming the way goods move around every local node in the supply chain by connecting shippers and commercial truck drivers with mobile technology. We are solving complex, real-world problems every day, and giving full transparency to the shipping process. 

AI Engineer- Rapid Prototyping & Automation

Cargomatic is seeking a highly hands-on AI Engineer who thrives in fast-paced environments and is passionate about rapid prototyping and deploying standalone AI-driven applications. This role focuses on building agentic AI systems and automation tools that can operate independently, integrate with our ecosystem, and deliver immediate business value.

You will work at the intersection of AI, product development, and infrastructure- quickly turning ideas into working prototypes and scaling the most promising solutions into production.

Key Responsibilities:

• Rapidly design, prototype, and deploy standalone AI applications that solve real-world logistics and operational challenges
• Build and implement agentic AI systems capable of autonomous decision-making and task execution
• Develop AI-powered automation tools to streamline workflows across operations, customer experience, and internal processes
• Leverage modern LLM ecosystems, including Claude-based and code-first AI frameworks, to build intelligent agents and workflows
• Integrate LLMs, APIs, and data pipelines into production-ready services
• Collaborate with product, engineering, and operations teams to identify high-impact opportunities for AI solutions
• Iterate quickly based on feedback, performance metrics, and evolving business needs
• Ensure scalability, reliability, and security of AI systems in production environments
• Stay current with advancements in AI/ML, especially in agent frameworks, Claude/OpenAI ecosystems, and automation tooling (e.g., n8n)
• Implement guardrails, validation layers, monitoring, and evaluation frameworks to mitigate hallucination, prompt injection, and data security risks.
• Collaborate cross-functionally with Product, Engineering, and Operations to translate business needs into scalable AI-enabled solutions.
• Contribute to architectural standards, technical best practices, and innovation initiatives.

Preferences:

• Strong product builder mindset with an ability to prioritize high-impact solutions
• 3+ years of experience in software engineering, with a focus on AI/ML or automation
• Proven experience building and deploying AI-powered applications or prototypes end-to-end
• Strong understanding of agentic AI concepts, LLMs, and modern AI frameworks
• Hands-on experience with Claude (Anthropic), OpenAI, or similar LLM APIs, including prompt design and orchestration
• Experience with code-based AI frameworks (e.g., Claude tool use / function calling, LangChain, AutoGen, CrewAI, or similar)
• Experience building or orchestrating workflows using n8n (or similar tools like Zapier, Temporal, Airflow)
• Experience with event-driven architectures and real-time systems
• Familiarity with vector databases and retrieval-augmented generation (RAG)
• Proficiency in backend development using Node.js
• Experience with frontend frameworks such as React for building lightweight interfaces
• Hands-on experience with cloud infrastructure, particularly AWS (Lambda, ECS, S3, etc.)
• Familiarity with databases such as MongoDB and RDS (PostgreSQL/MySQL)
• Experience integrating third-party APIs and building microservices
• Ability to move quickly from concept → prototype → production
• Active GitHub contributions or demonstrated passion for emerging technologies in AI and data systems.

Benefits & Perks:

• Competitive compensation
• Medical, dental, and vision benefits
• 401K company match program
• Flexible paid time off (PTO) and paid holiday

The Safety Processing team is responsible for the systems that power Discord's ability to detect, review, and enforce against harmful content at scale. We build the infrastructure and decision systems that enable accurate, efficient, and fair content moderation across all of Discord. We're looking for a Senior Software Engineer who can handle complex, multi-milestone projects and deliver high-quality systems that protect millions of users daily.

As a Senior Engineer on Safety Processing, you'll take full ownership of projects from initial design through post-launch monitoring and iteration. You'll work on challenging problems at the intersection of automation, large-scale distributed systems, and content safety. You'll help build automated decision systems that scale our review capacity by 10x, develop enforcement infrastructure that handles millions of decisions per day, or architect systems that centralize and simplify safety signal processing. You'll collaborate closely with Trust & Safety operations, ML teams, Policy, and product partners to deliver solutions that make Discord safer while maintaining our commitment to user experience. You'll deliver lovable products while maintaining Discord's high quality bar, utilizing 80/20 thinking and a user-centric approach. You'll embody a growth mindset, diving into new code and technologies to deliver safety solutions that protect millions of users daily. This person reports to the Engineering Manager of Safety Processing.

This role offers the opportunity to work on systems that directly impact user safety, tackle novel technical challenges in content moderation at scale, and help shape the future of how Discord keeps communities safe.

What You'll Be Doing:

• Own complex safety infrastructure projects end-to-end, from initial design through post-launch monitoring and iteration
• Build and maintain critical systems for automated content review, enforcement, and safety signal processing at massive scale
• Apply an adversarial mindset to your work, thinking through security, abuse scenarios, edge cases, and scalability concerns to protect Discord's users
• Collaborate with Trust & Safety, ML, Policy, and product teams to understand requirements and deliver effective safety solutions
• Break down complex, multi-milestone projects into smaller work streams while managing stakeholders and dependencies across teams
• Debug and resolve issues within the team's codebase and adjacent systems, participating in on-call rotations
• Contribute to technical design discussions and documentation, writing RFCs
• Help establish best practices and maintain the team's quality bar through code reviews and mentorship

What You Should Have:

• 4+ years of professional software engineering experience with a focus on backend services and infrastructure
• Strong programming skills in Python
• Experience building and operating distributed systems and production services at scale
• Demonstrated ability to own projects end-to-end and deliver results on time
• Strong debugging skills and ability to navigate complex codebases
• Excellent collaboration skills and ability to work effectively with cross-functional partners
• Experience working in larger engineering organizations with multiple teams and stakeholders
• A quality-centered mindset with attention to the right details at every stage of development
• Demonstrated adversarial thinking - ability to anticipate misuse, edge cases, and system vulnerabilities
• Experience with distributed systems concepts and cloud platforms (GCP/AWS)
• Experience being in 24/7 on-call rotations
• Strong collaboration and communication skills

Bonus Points:

• Experience with content moderation, trust & safety, or related problem domains
• Experience with workflow automation or decision systems
• Experience with ML/LLM integration and prompt engineering
• Experience with observability tools, metrics, and monitoring systems at scale
• Experience with cloud platforms (GCP/AWS)
• A strong passion for Discord and making online communities safer

Candidates must reside in or be willing to relocate to the San Francisco Bay Area (Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma counties). Relocation assistance may be available.

The US base salary range for this full-time position is $196,000 to $220,500 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.