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 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

About the Role

We're hiring an AI Engineer to work on the AI core of Mill Commercial — the computer vision and agentic systems that turn a stream of food waste into operational intelligence for commercial kitchens. Mill Commercial integrates a camera and onboard compute directly into our high-capacity food recycler; models running on the edge identify, classify, and quantify food scraps at the point of generation, and our vision pipeline turns that signal into procurement and operational guidance for large food service operators.

You'll join a small AI team, building the data and training pipeline that produces our edge CV models, designing the cloud-side evaluation that tells us whether those models are good enough to ship, and helping build the agentic, LLM-driven product features that turn raw waste data into customer-facing insights and recommendations. This is a hands-on senior IC role for someone who's equally comfortable fine-tuning a segmentation model, prompting a VLM, and wiring an agent into a product feature.

What You'll Do

• Build and manage the end-to-end ML training pipeline: data ingestion from deployed kitchen units, ground truth generation, annotation tooling (including foundation-model-assisted labeling), training, evaluation, and retraining cycles.
• Train and evaluate segmentation, classification, and mass-estimation models for the Mill Commercial camera pipeline — from prompting foundation models to fine-tuning ConvNets and VLMs.
• Build the cloud-side evaluation harness that tells us how our shipped edge models are actually performing in the field — automated, reproducible, and aligned to product accuracy targets across food types, kitchen environments, and deployment configurations.
• Own MLOps: reproducible training, experiment tracking, model versioning, and automated evaluation against product-defined accuracy targets.
• Export and validate models for deployment to edge devices, working closely with the edge team on optimization, quantization, and integration.
• Help design and build the LLM- and agent-powered product features that consume waste characterization data and turn it into customer-facing recommendations — purchasing suggestions, anomaly explanations, operational nudges. Define how agents call tools, ground in customer data, and stay reliable in production.
• Analyze failure cases systematically — unfamiliar food classes, novel kitchen environments, challenging lighting and clutter conditions — and drive the data and modeling decisions that close accuracy gaps.

What We're Looking For

• Strong fundamentals in computer vision and deep learning — segmentation, detection, classification, tracking. You understand the architectures well enough to make informed choices.
• Fluency with modern ML approaches — VLMs, LLMs, foundation models, and agentic systems — alongside classical deep learning. You know when to fine-tune a ConvNet, when to prompt a VLM, and when to wire up an agent, and you understand the practical realities of putting any of them into a product.
• Experience building ML training pipelines and data annotation systems at scale.
• Experience evaluating ML models rigorously — designing metrics, building the eval harness, and using results to drive product decisions rather than just publish a number.
• Proficiency with cloud ML infrastructure (AWS or equivalent) — you've managed training jobs, data pipelines, and experiment workflows in production.
• Familiarity with cloud-to-edge model deployment.
• Clear, direct communication — you can explain tradeoffs to non-technical stakeholders, push back honestly when you disagree, and write docs that others can follow.
• Genuine interest in applying AI to food waste reduction and sustainability. This is a mission-driven product and we want people who care about the mission.

Software skills: Python, PyTorch, OpenCV. Strong familiarity with MLOps on AWS infrastructure. Experience with LLM and agent frameworks. Google Cloud / Gemini experience is a plus.

Nice to Have

• Experience with video understanding (temporal consistency, tracking, video segmentation)
• Experience with foundation models for data annotation
• Experience with MLOps tooling (Weights & Biases, MLflow, SageMaker, or equivalents)
• Experience shipping LLM- or agent-powered features in a consumer or B2B product
• Hardware / IoT product experience, particularly with computer vision and cameras for embedded systems

The estimated base salary range for this position is $240 to $280k, which does not include the value of benefits or a potential equity grant. A wide range of factors are considered in making compensation decisions, including but not limited to skill sets, market conditions, experience and training, licensure and certifications, and business and organizational needs. At Mill, it is not typical for an individual to be hired at or near the top of the range for their role.

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. 

Global Data Privacy Notice for Job Candidates and Applicants:

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.

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.

Summary

We are looking for a software engineer to build internal tools that help our battery algorithm team work faster and smarter. You will develop applications for test data analysis, visualization, and documentation, incorporating AI powered capabilities where they accelerate engineering workflows. This is a software engineering role: you will write clean, maintainable code, build intuitive interfaces, and integrate modern AI services into practical tools that engineers actually use.

What You Will Do

• Build Python based applications for analyzing and visualizing large scale battery test data, including time series datasets.
• Develop web based GUIs that let engineers explore, filter, and interact with test results.
• Integrate LLM APIs (e.g., OpenAI, Anthropic) into workflows to automate documentation, extract context from requirement sheets, change reports, and code repositories.
• Create data pipelines that pull from multimodal sources and present actionable insights.
• Collaborate with algorithm engineers and test engineers to understand their pain points and build tools that solve real problems.
• Continuously improve tooling based on user feedback and evolving team needs.

Minimum Qualifications

• B.Sc. or M.Sc. in Computer Science, Electrical Engineering, Mechanical Engineering, or related field.
• 3+ years of professional software development in Python, including data analysis and visualization libraries (pandas, matplotlib, plotly, etc.)
• Experience building web based tools or applications with a frontend component (e.g., React, Streamlit, Dash, or similar)
• Strong debugging and problem solving skills.
• Comfortable working with APIs and integrating third party services.

Preferred Qualifications

• Experience integrating LLM APIs or AI services into applications (prompt engineering, API orchestration, retrieval augmented generation)
• Familiarity with time series data analysis
• Experience with document automation or generation (Word, PDF, slides)
• Exposure to battery management systems or embedded systems workflows• Experience with CI/CD, version control best practices, and collaborative development environments

At.Monks, we believe in fostering an environment where a diversity of perspectives can thrive. We proactively work to design hiring processes that promote equity and inclusion while mitigating bias. We celebrate diversity and are committed to building a team that reflects the communities we serve. We welcome and encourage qualified applicants, from all backgrounds, who are excited to contribute to our mission.  

What We Offer

.Monks has provided a compensation range that represents its good faith estimate of what Media.Monks may pay for the position at the time of posting. .Monks may ultimately pay more or less than the posted compensation range. The salary offered to the selected candidate will be determined based on job-related factors, but not based on a candidate’s sex or any other protected status.

Cupertino, CA

ABOUT THE TEAM:

ArsenalOS is the digital backbone of Anduril’s hardware enterprise. It connects the full lifecycle, from concept to build to field feedback, into one operating environment built for speed, traceability, autonomy, and continuous improvement. That environment includes not just the software used to design, plan, and execute work, but also the factory-facing infrastructure that connects operators, machines, test systems, and OT networks into the same adaptive Build Chain. It is not a support function, but rather a strategic investment by Anduril that the operating system of the hardware lifecycle is how we win. It will be one of the mechanisms by which Anduril out-builds, out-adapts, and out-scales the traditional defense industrial base.

ABOUT THE JOB:

We are looking for a Staff Software Engineer to join our QualityOS team within Forge MES (Manufacturing Execution System). As a Staff Engineer, you will set the technical direction and architectural standards. You'll architect and implement mission-critical distributed systems that scale Anduril's manufacturing operations while maintaining the technical bar for reliability, performance, and maintainability.

Your impact will span beyond the immediate team. You'll serve as a technical bridge between the QualityOS product team and our Platform/Foundations organization, ensuring we build on solid infrastructure while influencing platform capabilities to meet manufacturing needs. You'll represent the quality domain in broader MES architectural decisions, contributing to technical strategy that affects multiple product teams.

We're looking for someone who combines deep technical expertise with strong collaborative instincts—someone who can dive into complex distributed systems, establish patterns that others follow, and drive consensus across engineering teams. You'll balance hands-on technical execution on critical features with raising the technical standards of the team through architecture reviews, code quality, and operational excellence. Your decisions will have lasting impact on how Anduril scales manufacturing quality systems into a next-generation defense company.

WHAT YOU'LL DO

Technical Architecture & Execution:

• Define and drive technical architecture for QualityOS - make decisions on system design, scalability patterns, integration strategies, and platform vs. build tradeoffs that shape team execution
• Architect and implement complex distributed systems - build mission-critical services, APIs, and tooling that enable safe, fast delivery across manufacturing quality workflows
• Lead by example with engineering excellence - establish patterns through hands-on work: comprehensive testing, deployment safety (blue/green/canary), infrastructure as code, observability, and operational rigor

Cross-Team Influence & Collaboration:

• Bridge product and platform teams - collaborate with Platform/Foundations to shape shared infrastructure based on QualityOS needs while driving adoption of platform capabilities
• Partner across MES product teams - integrate QualityOS into cohesive manufacturing experiences, evolve data models across quality/production domains, and drive technical consensus on cross-cutting concerns
• Represent quality domain technically - work with architecture, security, operations, and infrastructure teams to ensure quality requirements influence broader technical decisions

Team & Technical Standards:

• Raise the technical bar for the team - through rigorous code review, architecture discussions, establishing shared ownership models, and improving practices that balance velocity with correctness
• Remove friction and unblock execution - identify systemic technical issues, eliminate single points of failure, and create leverage through automation and improved tooling

REQUIRED QUALIFICATIONS

• 12+ years of experience in a software engineering role building products in fast-paced environments
• Proven ability to influence technical direction across teams - drive architectural consensus, build alignment, and lead technical initiatives beyond a single team
• Experience working with large enterprise applications and platforms with high availability requirements
• Strong full-stack capabilities with expertise in modern web technologies - JavaScript/TypeScript, React, and web frameworks (Next.js, Remix, etc.)
• User-focused engineering mindset - ability to translate user needs into technical solutions while balancing user experience with engineering constraints
• Excellent communication skills, able to influence stakeholders, translate ambiguous requirements and build cross-team alignment.
• U.S. Person status is required as this position needs to access export controlled data

PREFERRED QUALIFICATIONS

• We encourage people from all backgrounds to apply but our tech stack uses AWS, Typescript, and React/Remix so familiarity with all of these tools will be particularly helpful
• Experience in hyper growth startup-like environments. Demonstrated successes in scaling and maturing software development processes, team culture and methods, and ability to balance short-term and long-term trade offs
• Manufacturing/quality domain knowledge - experience with quality management systems (QMS), manufacturing execution systems (MES), or incident management platforms
• Experience in defense, autonomy, robotics, or mission-critical systems (helpful but not required)
• Experience with AI/LLM integration - leveraging state-of-the-art models and agentic tooling in production software development
• Eligible to obtain and maintain a U.S. TS/SCI clearance

Role Overview

We are seeking a Sr. Technical Product Manager to lead the strategy and execution of data product, AI/ML system, AI-powered tooling, and automation initiatives across Patient Experience and Commercial Operations functions. This role is focused on improving how patients navigate testing and billing while enabling operational teams to efficiently progress cases from order to completion. You will play a crucial part in supporting initiatives to reduce friction, improve patient trust, and increase operational efficiency, ultimately driving better conversion, collections, and experience.

This role focuses on building, scaling, and leveraging platforms and products that power decision intelligence and activity orchestration across these domains. You will work in close collaboration with domain leaders while building through centralized Data & AI organization platforms, standards, and governance. You will own the full product lifecycle from discovery through production, ensuring solutions are adopted, trusted, and deliver measurable business impact. In doing so, you will work hands-on as an empowered builder of AI and software solutions to improve workflow efficiency, productivity, and quality for the teams you support.

This is a technical product role requiring fluency in data systems, modern data platforms, ML, and AI implementation patterns (and the ability and drive to build with them directly), combined with strong experience and stakeholder intuition across the associated functions. The role has direct ownership of high-impact initiatives that deeply influence organizational success.

What You’ll Do

Strategy & Roadmap

• Define and own the Data & AI product strategy and roadmap for the Patient Experience + Commercial Operations pod by deeply partnering with business leaders to proactively identify high-impact opportunities, shape problem definitions, and drive aligned priorities
• Translate ambiguous business problems (e.g., stuck cases, fragmented patient communication, support inefficiencies, billing friction) into clear product direction and measurable outcomes
• Own the line between 'what the business needs' and 'what gets built' end-to-end

Discovery, Experimentation, & Requirements

• Develop deep context on the domain so you can proactively propose solutions rather than field requests
• Be hands-on with data: query datasets, review schemas, and validate assumptions through analysis
• Lead end-to-end product discovery with interviews, workflow mapping, data assessments, ROI modeling, etc.
• Define clear product requirements (PRDs, user stories, acceptance criteria) and success metrics
• Design and run experiments to validate product performance and measure causal impact
• Establish leading indicators and KPIs for proactive product and process health assessments

Delivery, Data, & ML Lifecycle

• Partner with data and AI/ML engineering resources to deliver scalable products and capabilities
• Guide development of robust data pipelines and unified data models (360° views across key entities)
• Own the end-to-end ML lifecycle: feature definition, evaluation, deployment, monitoring, drift detection, and retraining
• Ensure training–serving consistency, model versioning, and clear deployment decision gates
• Establish strong observability across data pipelines and models (data quality, latency, reliability, cost)

AI Productization & Hands-On Building

• Define and implement AI product patterns, including agentic workflows and tool/function-calling integrations
• Build process automations and internal tools that improve workflow efficiency, productivity, and output quality for the teams you support
• Establish evaluation frameworks for LLM-powered features (faithfulness, relevance, safety, cost, latency)
• Implement prompt strategies, guardrails, and continuous evaluation pipelines

Governance, Compliance, & Data Quality

• Ensure products meet regulatory and compliance requirements
• Champion data quality, lineage, and reliability through data contracts and observability standards
• Maintain strong documentation practices (e.g., model cards, dataset documentation, audit trails)
• Partner with governance teams (Security, Legal, Compliance, AI Governance) to operationalize AI responsibly

Adoption, Change Management, & Impact

• Launch products with supporting enablement activities to ensure solutions are embedded in workflows with confidence
• Partner with stakeholders to integrate products into proactive, day-to-day decision-making
• Monitor product usage, performance, and business outcomes to iterate based on data and feedback
• Quantify and communicate impact (e.g., revenue lift, cost reduction, cycle time improvements, case completion turnaround)
• Influence Patient Experience and Commercial Operations stakeholders through delivery, not authority

Qualifications

Required

• 7+ years of relevant experience (e.g., product management, applied AI/ML engineering, technical founder, forward-deployed engineering), including 3+ years building data products, AI/ML systems, or related platforms
• Demonstrated domain fluency in Patient Experience and/or Commercial Operations
• Strong understanding of patient journeys, support channels (e.g., chat, voice, call centers), and operational workflows that drive conversion and test completion
• Familiarity with key domain-relevant tooling (e.g., patient portals, support platforms) and associated data
• Strong technical capability (e.g., comfortable scripting, performing EDA, with AI-aided application development)
• Hands-on experience shipping LLM-powered features or automations (e.g., prompting, RAG, tool/function calling, agentic orchestration, evals)
• ML/MLOps literacy (evaluation metrics, experimentation, feature stores, CI/CD, monitoring, drift)
• Familiarity with modern data stacks (e.g., Snowflake, dbt, AWS/SageMaker, Airflow/Dagster)
• Strong stakeholder leadership and communication skills, with the ability to work across technical and business teams
• Experience working in regulated environments (e.g., healthcare, life sciences, fintech)

Preferred

• Experience in healthcare, diagnostics, life sciences, and/or digital health
• Familiarity with healthcare data domains and systems, including patient, provider, payer, claims, billing, and clinical trial data
• Experience with vendor evaluation, platform selection, or external AI tooling ecosystems
• Advanced degree in a technical and/or business discipline

What Success Looks Like

• Production-grade data and AI products are deployed and embedded in day-to-day decision-making workflows
• Process automations and internal tools you build are reducing manual effort and improving output quality across the teams you support
• Measurable improvements seen in key business metrics (e.g., case completion turnaround time, patient satisfaction, cost-to-serve)
• Reliable, high-quality data foundations connect patient, provider, clinical, operational, and billing/financial insights end-to-end
• AI systems are continuously monitored, evaluated, and improved with measurable business impact
• Stakeholders trust and adopt implemented solutions across both corporate and business-unit teams
• Internal teams have transparent access to the function's roadmap, trust in delivery against it, and visibility into the evaluation logic that prioritizes initiatives based on their impact to organizational goals

Role Overview

We are seeking a Sr. Technical Product Manager to lead the strategy and execution of data product, AI/ML system, AI-powered tooling, and automation initiatives across the go-to-market and operational teams embedded within Natera’s core business units (i.e., Oncology, Women’s Health, Organ Health), including Sales, Marketing, and Medical stakeholders. 

This role focuses on building, scaling, and leveraging platforms and products that power decision intelligence and activity orchestration across these domains. You will work in close collaboration with ‘S&M + GM’ leaders while building through centralized Data & AI organization platforms, standards, and governance. You will own the full product lifecycle from discovery through production, ensuring solutions are adopted, trusted, and deliver measurable business impact. In doing so, you will work hands-on as an empowered builder of AI and software solutions to improve workflow efficiency, productivity, and quality for the teams you support.

This is a technical product role requiring fluency in data systems, modern data platforms, ML, and AI implementation patterns (and the ability and drive to build with them directly), combined with strong experience and stakeholder intuition across Sales, Marketing, Medical, and related functions.

This role sits at the intersection of business impact and technical depth, with deep visibility into commercial performance and executive decision-making. You will have direct ownership of high-impact initiatives fueling overall organizational success.

What You’ll Do

Strategy & Roadmap

• Define and own the Data & AI product strategy and roadmap for the S&M + GM pod by deeply partnering with business leaders to proactively identify high-impact opportunities, shape problem definitions, and drive aligned priorities
• Translate ambiguous business problems (e.g., churn risk, campaign performance, clinical profile segmentation, next-best-action orchestration) into clear product direction and measurable outcomes
• Own the line between ‘what the business needs’ and ‘what gets built’ end-to-end

Discovery, Experimentation, & Requirements

• Develop deep context on the domain so you can proactively propose solutions rather than field requests
• Be hands-on with data: query datasets, review schemas, and validate assumptions through analysis
• Lead end-to-end product discovery with interviews, workflow mapping, data assessments, ROI modeling, etc.
• Define clear product requirements (PRDs, user stories, acceptance criteria) and success metrics
• Design and run experiments to validate product performance and measure causal impact
• Establish leading indicators and KPIs for proactive product and process health assessments

Delivery, Data, & ML Lifecycle

• Partner with data and AI/ML engineering resources to deliver scalable products and capabilities
• Guide development of robust data pipelines and unified data models (360° views across key entities)
• Own the end-to-end ML lifecycle: feature definition, evaluation, deployment, monitoring, drift detection, and retraining
• Ensure training–serving consistency, model versioning, and clear deployment decision gates
• Establish strong observability across data pipelines and models (data quality, latency, reliability, cost)

AI Productization & Hands-On Building

• Define and implement AI product patterns, including agentic workflows and tool/function-calling integrations
• Build process automations and internal tools that improve workflow efficiency, productivity, and output quality for the teams you support
• Establish evaluation frameworks for LLM-powered features (faithfulness, relevance, safety, cost, latency)
• Implement prompt strategies, guardrails, and continuous evaluation pipelines

Governance, Compliance, & Data Quality

• Ensure products meet regulatory and compliance requirements
• Champion data quality, lineage, and reliability through data contracts and observability standards
• Maintain strong documentation practices (e.g., model cards, dataset documentation, audit trails)
• Partner with governance teams (Security, Legal, Compliance, AI Governance) to operationalize AI responsibly

Adoption, Change Management, & Impact

• Launch products with supporting enablement activities to ensure solutions are embedded in workflows with confidence
• Partner with stakeholders to integrate products into proactive, day-to-day decision-making
• Monitor product usage, performance, and business outcomes to iterate based on data and feedback
• Quantify and communicate impact (e.g., revenue lift, cost reduction, cycle time improvements, forecasting accuracy)
• Influence across Sales, Marketing, Medical, and GM stakeholders through delivery, not authority

Qualifications

Required

• 7+ years of relevant experience (e.g., product management, applied AI/ML engineering, technical founder, forward-deployed engineering), including 3+ years building data products, AI/ML systems, or related platforms
• Demonstrated domain fluency in Sales, Marketing, Field Medical, and/or related commercial/GTM functions 
• Strong understanding of sales funnel, marketing funnel, medical affairs funnel, and related funnels to relate product ideas to the overall opportunity landscape
• Familiarity with key domain-relevant tooling (e.g., Salesforce) and associated data 
• Strong technical capability (e.g., comfortable scripting, performing EDA, with AI-aided application development)
• Hands-on experience shipping LLM-powered features or automations (e.g., prompting, RAG, tool/function calling, agentic orchestration, evals)
• ML/MLOps literacy (evaluation metrics, experimentation, feature stores, CI/CD, monitoring, drift)
• Familiarity with modern data stacks (e.g., Snowflake, dbt, AWS/SageMaker, Airflow/Dagster)
• Strong stakeholder leadership and communication skills, with the ability to work across technical and business teams
• Experience working in regulated environments (e.g., healthcare, life sciences, fintech)

Preferred

• Experience in healthcare, diagnostics, life sciences, and/or digital health
• Familiarity with healthcare data domains and systems
• Experience with vendor evaluation, platform selection, or external AI tooling ecosystems
• Advanced degree in a technical and/or business discipline

What Success Looks Like

• Production-grade data and AI products are deployed and embedded in day-to-day decision-making workflows
• Process automations and internal tools you build are reducing manual effort and improving output quality across the teams you support
• Measurable improvements seen in key business metrics (e.g., increased sales efficiency, better campaign performance)
• Reliable, high-quality data foundations connect patient, clinical, financial, and commercial insights end-to-end
• AI systems are continuously monitored, evaluated, and improved with measurable business impact
• Stakeholders trust and adopt implemented solutions across both corporate and business-unit teams
• Internal teams have transparent access to the function’s roadmap, trust in delivery against it, and visibility into the evaluation logic that prioritizes initiatives based on their impact to organizational goals
  
  

#LI-DNI

Applicants must be authorized to work for any employer in the U.S. without sponsorship. We are unable to provide sponsorship for work visas of any kind at the time of hire, or at any point during employment. This includes, but is not limited to: F1-OPT, F1-CPT, H-1B, TN, J-1, etc.

Location: Live in or able to relocate to San Francisco / San Jose area

Your Role:

Tenable is not only building great products and carving out a completely new category, but we are also building a world-class engineering culture committed to hiring the very best.

We are looking for a Senior Software Engineer to join a founding initiative within our engineering organization. In this role, you will help design and implement the Agentic AI Platform, the orchestration layer and nervous system that enables autonomous agents to reason, plan, and execute complex security workflows across our Exposure Management ecosystem.

This is a hands-on engineering role with broad impact. You will not just be "using" LLMs; you will be building the distributed systems, state machines, and tooling that transform generative models into reliable, enterprise-grade agents. 

While you will work from home the majority of your time, there may be an expectation to gather for in-person meetings on occasion. 

Your Opportunity:

• Build the Agentic Backbone: Architect and implement the backend services that power multi-agent workflows. You will build systems that allow AI agents to decompose complex user requests, manage state, and execute tasks across distributed microservices.
• Orchestration & Workflow Automation: Design scalable workflow engines and "human-in-the-loop" systems. You will enable agents to perform long-running investigations and remediation tasks, balancing autonomy with control.
• Bridge AI & Enterprise Infrastructure: Create the integration layer between modern Python-based AI frameworks and Tenable’s robust JVM-based microservices architecture.
• Reliability & Guardrails: Implement verification layers, citations, and security guardrails to ensure agents operate deterministically and safely. You will treat "prompts" as code and model outputs as untrusted input that requires validation.
• Tooling & RAG: Build advanced Retrieval-Augmented Generation (RAG) pipelines and "Tool Use" capabilities, allowing agents to query databases, call internal APIs, and synthesize data from disparate sources.
• Lead Technical Direction: Collaborate with researchers and product leads to define the roadmap for AI orchestration. Champion best practices for MLOps, agent evaluation, and system observability.

What You’ll Need:

• B.S. or M.S. in Computer Science, Engineering, or a related field, or equivalent practical experience.
• 5+ years of software engineering experience (7+ for Staff level), with a strong background in building backend systems, APIs, and platforms.
• Agentic AI Expertise: Hands-on experience building AI agents and autonomous workflows using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or Pydantic AI.
• Location: Live in or able to relocate to San Francisco / San Jose area
• Polyglot Proficiency: Strong programming skills in Python (essential for AI/ML ecosystems) with experience in, or a willingness to work with, JVM-based languages (Java, Kotlin, or Scala) for high-scale platform components.
• Distributed Systems: Experience designing event-driven architectures, managing concurrency, and building fault-tolerant services (e.g., using Kafka, gRPC, REST).
• Data Fluency: Proficiency with Relational Databases (PostgreSQL) and experience with Vector Databases (e.g., Pinecone, Weaviate, Milvus) or search engines (Elasticsearch).
• Builder Mindset: A self-starter who thrives in ambiguity and is passionate about taking AI from "prototype" to "production-grade."

And Ideally:

• LLM Ops & Evaluation: Experience designing frameworks to evaluate agent performance (accuracy, latency, cost) and implementing CI/CD for AI workflows.
• Cloud Native: Experience deploying and scaling services in AWS using Docker and Kubernetes.
• Graph & Search: Familiarity with Knowledge Graphs or advanced search algorithms to improve agent reasoning.
• Security Context: Understanding of cybersecurity concepts (vulnerability management, cloud security) is a plus, but not required if you are a strong systems engineer.

#LI-LP1

The AGI (Artificial General Intelligence) Computing Lab is dedicated to solving the complex system-level challenges posed by the growing demands of future AI/ML workloads. Our team is committed to designing and developing scalable platforms that can effectively handle the computational and memory requirements of these workloads while minimizing energy consumption and maximizing performance. To achieve this goal, we collaborate closely with both hardware and software engineers to identify and address the unique challenges posed by AI/ML workloads and to explore new computing abstractions that can provide a better balance between the hardware and software components of our systems. Additionally, we continuously conduct research and development in emerging technologies and trends across memory, computing, interconnect, and AI/ML, ensuring that our platforms are always equipped to handle the most demanding workloads of the future. By working together as a dedicated and passionate team, we aim to revolutionize the way AI/ML applications are deployed and executed, ultimately contributing to the advancement of AGI in an affordable and sustainable manner. Join us in our passion to shape the future of computing!

This role is being offered under the AGICL lab as a part of DSRA. We are a research-driven systems lab working at the intersection of large language models, accelerator hardware, and high-performance software stacks. Our mission is to design, prototype, and optimize next-generation AI systems through tight hardware–software co-design.

Our team works hands-on with cutting-edge accelerator hardware, experimental memory systems, and emerging domain-specific languages (DSLs). We build and optimize a Triton-based software stack that pushes the limits of performance, efficiency, and scalability for modern LLM workloads.

We are looking for a Senior AI Systems Engineer with deep experience in high performance Triton kernel development on modern accelerators. In this role, you will design, analyze, and optimize performance-critical kernels used in large scale LLM inference and training pipelines. You will work closely with hardware architects, compiler engineers, and ML researchers to identify performance bottlenecks, interpret profiling data, and co-design solutions that span software and hardware boundaries.

This role is ideal for engineers who enjoy working close to the hardware stack while still reasoning deeply about model level abstractions.

Location:  Daily onsite presence at our San Jose, CA office / U.S. headquarters in alignment with our Flexible Work policy.

What You’ll Do

• Design, implement, and optimize high-performance Triton kernels for LLM workloads on existing accelerators.
• Analyze kernel performance using profiling tools; interpret metrics such as latency, throughput, occupancy, memory bandwidth, and compute utilization.
• Identify performance bottlenecks in kernel design (e.g., memory access patterns, synchronization, tiling strategies) and propose concrete optimizations.
• Work across the stack; from model architecture to kernel implementation—to ensure end-to-end performance efficiency.
• Collaborate with hardware and compiler teams on hardware–software co-design, providing feedback that influences future accelerator and DSL designs.
• Prototype and evaluate kernel optimizations using upcoming DSLs and experimental compiler flows.
• Contribute to the evolution of a Triton-based software stack used for cutting-edge research and production-grade experimentation.
• Document design decisions, performance trade-offs, and optimization strategies clearly for internal and external stakeholders.

What You Bring

• Bachelor’s with 5+ years, or Master’s with 3+ years, or PhD's with 0+ years of industry experience.
• Strong experience writing high-performance Triton kernels for GPUs or other accelerators.
• Solid understanding of LLM fundamentals, including attention mechanisms, transformer architectures, and inference/training workflows.
• Deep knowledge of accelerator hardware architecture, including:  Memory hierarchies (HBM, SRAM, caches).
• Proven ability to read and interpret profiling data and performance counters.
• Experience diagnosing and resolving performance bottlenecks in kernel-level code.
• Strong systems programming skills in Python and low-level performance-oriented programming paradigms.
• Experience with hardware–software co-design or compiler-assisted optimization.
• Familiarity with FlashAttention, fused kernels, MoE kernels, and different attention mechanisms.
• Experience working with emerging or experimental domain-specific languages (DSLs) for accelerator programming.
• Background in ML systems, compilers, or performance engineering.
• Prior experience working with different accelerator backends (including but not limited to CUDA).
• Opportunity to work on cutting-edge accelerator hardware and experimental software stacks.
• Direct impact on the performance and design of next-generation AI systems.
• A highly collaborative environment spanning hardware, systems, and ML research.
• Flexibility to publish, prototype, and influence future hardware and software directions.
• Ability to work effectively in cross-functional, research-oriented environments.
• Strong analytical and problem-solving skills.
• You’re inclusive, adapting your style to the situation and diverse global norms of our people.
• An avid learner, you approach challenges with curiosity and resilience, seeking data to help build understanding.
• You’re collaborative, building relationships, humbly offering support and openly welcoming approaches.
• Innovative and creative, you proactively explore new ideas and adapt quickly to change.

#LI-VL1

Job Title: Principal engineer, AI Serving Framework Architect (Software)

What You’ll Do    

The Architecture Research Lab (ARL) focuses on addressing fundamental system-level bottlenecks in modern AI, particularly in memory capacity/bandwidth and system-scale communication. By leveraging Samsung’s world-class memory technologies, ARL explores and defines next-generation AI system architectures that deliver step-function improvements in performance, efficiency, and scalability.
We are seeking a Principal AI System Architect who will play a key role in bridging AI workloads, system architecture, and hardware design. In this role, you will develop system-level performance models, drive architecture-level design decisions, and propose forward-looking AI system architectures that shape Samsung’s long-term AI platform strategy.

Location: Daily onsite presence at our San Jose office in alignment with our Flexible Work policy

Job ID: 42853

• As a Tech Lead, leading research teams in Korea and proposing technical direction
• Research on dynamic scheduling methodologies for maximizing AI inference performance in multi-rack scale memory-centric systems, comprised of heterogeneous compute-capable memory and hierarchical memory
• Investigating methods to accelerate search operations in RAG’s vector DB and AI Agent’s knowledge-graph by leveraging compute-capable memory
• Studying strategies for optimally placing KVCache and a vector DB in hierarchical memory to minimize frequent SSD accesses and reduce IO stalls
• Proposing SW design for implementing the derived optimization algorithms on open-source platforms such as vLLM

What You Bring

• PhD in Computer Science or a related field with 10+ years of experience in AI Serving Framework for large-scale computing, with focusing on the AI workloads. 
• Led a project to build and optimize a Large Language Model (LLM) Inference Software Stack on a multi-rack scale system to deliver AI Inference services to over 100,000 users. 
• Extensive experience in designing AI Inference Software Stacks for heterogeneous devices.In-depth understanding of the internal architecture and operation mechanisms of inference engines such as vLLM. 
• Proficiency in AI Inference System Profiling and optimization. 
• Knowledge and practical experience with future AI workloads, including reasoning models, multi-modal solutions, AI agents, and world models. 
• Strong understanding of compute, memory, and networking bottlenecks in AI systems. 
• Required skillsets: PyTorch, Python, and C++ 
• A collaborative mindset, curiosity, and resilience in solving complex challenges. 
• Excellent verbal, presentation, and written communication skills. 
• (Nice to have) Native or fluent Korean speakers are preferred. 
• You’re inclusive, adapting your style to the situation and diverse global norms of our people. 
• You approach challenges with curiosity and resilience, seeking data to help build. Understanding.
• You’re collaborative, building relationships, humbly offering support and openly welcoming approaches. 
• Innovative and creative, you proactively explore new ideas and adapt quickly to change 

#LI-SF1

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

Everpure is seeking a talented and experienced Agentic AI Software Engineer to join our dynamic team in Santa Clara, CA. In this role, you will build production-grade agentic AI solutions that drive enterprise automation and digital transformation. You will design and deploy LLM-based services , implement strong prompt engineering techniques, guardrails, and model evaluation frameworks, and ensure secure, scalable delivery on AWS. This role focuses on building reliable, secure, and observable AI systems integrated with enterprise platforms.

WHAT YOU'LL DO

• Design and develop production-grade Agentic AI solutions using LLMs, multi-agent workflows, and RAG pipelines.
• Implement and refine Prompt Engineering strategies, including structured prompts, tool-calling, and agent orchestration to ensure reliable and deterministic AI behavior.
• Build secure backend services and REST APIs in Python, integrating AI agents with enterprise systems using microservices architecture.
• Establish robust guardrails, including output validation, fallback strategies, rate limiting, safe tool invocation, and human-in-the-loop patterns where appropriate.
• Develop and maintain model evaluation frameworks, including automated prompt testing, retrieval validation, regression testing, and performance benchmarking.
• Deploy and operate AI services on AWS, leveraging services such as EC2, S3, Lambda, RDS, and containerization using Docker and Kubernetes.
• Apply strong security best practices, including access control, data protection, audit logging, and secure API design.
• Ensure strong observability, monitoring, and reliability of AI-driven services in production.
• We are primarily an in-office environment and therefore, you will be expected to work from the Santa Clara, CA office in compliance with Everpure's policies, unless you are on PTO, or work travel, or other approved leave.

WHAT YOU BRING

• 3–6 years of professional software engineering experience building backend or distributed systems.
• Strong proficiency in Python and developing RESTful APIs.
• Hands-on experience building LLM-based or Agentic AI applications, including RAG, embeddings, and vector database integrations.
• Practical experience in Prompt Engineering and understanding of LLM behavior, limitations, and optimization techniques.
• Experience deploying and operating applications in AWS cloud environments.
• Experience implementing AI guardrails, model validation techniques, and production monitoring.
• Solid understanding of cloud-native security practices and secure system design.

Preferred Qualifications

• Experience with multi-agent orchestration frameworks or AI tool integration patterns.
• Familiarity with vector databases such as Pinecone, Weaviate, OpenSearch, or similar.
• Experience with CI/CD pipelines and containerized deployments using Docker and Kubernetes.
• Exposure to enterprise platform integrations such as ServiceNow, Snowflake, or similar systems.
• Familiarity with observability tools such as Datadog, Prometheus, or similar platforms.

#LI-ONSITE 

#LI-TH3

THE ROLE

Everpure is seeking a talented and experienced Agentic AI Software Engineer to join our dynamic team in Santa Clara, CA. In this role, you will build production-grade agentic AI solutions that drive enterprise automation and digital transformation. You will design and deploy LLM-based services , implement strong prompt engineering techniques, guardrails, and model evaluation frameworks, and ensure secure, scalable delivery on AWS. This role focuses on building reliable, secure, and observable AI systems integrated with enterprise platforms.

WHAT YOU'LL DO

• Design and develop production-grade Agentic AI solutions using LLMs, multi-agent workflows, and RAG pipelines.
• Implement and refine Prompt Engineering strategies, including structured prompts, tool-calling, and agent orchestration to ensure reliable and deterministic AI behavior.
• Build secure backend services and REST APIs in Python, integrating AI agents with enterprise systems using microservices architecture.
• Establish robust guardrails, including output validation, fallback strategies, rate limiting, safe tool invocation, and human-in-the-loop patterns where appropriate.
• Develop and maintain model evaluation frameworks, including automated prompt testing, retrieval validation, regression testing, and performance benchmarking.
• Deploy and operate AI services on AWS, leveraging services such as EC2, S3, Lambda, RDS, and containerization using Docker and Kubernetes.
• Apply strong security best practices, including access control, data protection, audit logging, and secure API design.
• Ensure strong observability, monitoring, and reliability of AI-driven services in production.
• We are primarily an in-office environment and therefore, you will be expected to work from the Santa Clara, CA office in compliance with Everpure's policies, unless you are on PTO, or work travel, or other approved leave.

WHAT YOU BRING

• 3–6 years of professional software engineering experience building backend or distributed systems.
• Strong proficiency in Python and developing RESTful APIs.
• Hands-on experience building LLM-based or Agentic AI applications, including RAG, embeddings, and vector database integrations.
• Practical experience in Prompt Engineering and understanding of LLM behavior, limitations, and optimization techniques.
• Experience deploying and operating applications in AWS cloud environments.
• Experience implementing AI guardrails, model validation techniques, and production monitoring.
• Solid understanding of cloud-native security practices and secure system design.

Preferred Qualifications

• Experience with multi-agent orchestration frameworks or AI tool integration patterns.
• Familiarity with vector databases such as Pinecone, Weaviate, OpenSearch, or similar.
• Experience with CI/CD pipelines and containerized deployments using Docker and Kubernetes.
• Exposure to enterprise platform integrations such as ServiceNow, Snowflake, or similar systems.
• Familiarity with observability tools such as Datadog, Prometheus, or similar platforms.

#LI-ONSITE

#LI-TH3

Senior Business Development Leader, AI Native Ecosystems & Strategic Influence

THE ROLE You will be the primary architect of Everpure’s "Pull-Through" strategy, ensuring the world’s most influential AI Native startups mandate Everpure™ as their foundational data layer. By moving upstream to influence technical and executive leadership, you will secure our place within $100M+ GPU contracts across Neoclouds and Hyperscalers. This high-impact role bridges the gap between disruptive AI engineering and global cloud infrastructure, establishing Everpure™ as the indispensable standard for the next generation of AI giants.

WHAT YOU’LL DO

• Establish Architectural Mandates: Build deep-rooted partnerships with C-suite and Engineering leaders at high-growth AI startups to get Everpure™ written into their "Standard Reference Architecture," ensuring our technology is a non-negotiable requirement for their production environments.
• Drive Ecosystem Orchestration: Collaborate with the Neocloud ecosystem (e.g., CoreWeave, Lambda) to integrate Everpure™ as a first-class citizen within their GPU-as-a-Service offerings, creating seamless "bring-your-own-storage" paths for customers.
• Execute Competitive Displacements: Outmaneuver niche storage players by positioning the reliability, power efficiency, and "Evergreen" model of the Everpure™ Platform as the only sustainable choice for large-scale LLM and RAG deployments.
• Influence Product Evolution: Serve as a strategic conduit between the AI startup ecosystem and Everpure’s internal AI/HPC product teams, ensuring our roadmap anticipates and solves for the extreme-scale requirements of emerging AI training loops.

WHAT YOU BRING

• Strategic Ecosystem Influence: Proven ability to navigate and influence the SF/NYC/Seattle AI startup landscape and Neocloud provider networks to secure high-impact, "lighthouse" partnerships.
• Technical AI Fluency: Deep understanding of AI infrastructure, including NVIDIA architectures, RDMA/RoCE fabrics, and the critical role of metadata performance in high-frequency AI training and inference.
• Business Transformation Expertise: Demonstrated success in executing complex, non-traditional business development motions that shift market perception and drive large-scale infrastructure adoption through strategic influence rather than high-volume transactions.
• Collaborative Leadership: Ability to lead cross-functional initiatives independently, acting as a facilitator between external executive stakeholders and internal engineering teams to resolve complex architectural challenges.

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.

The Impact You’ll Be Contributing to Moloco:

• We're seeking a software engineer to help us design, develop and maintain the backend of our state of the art Moloco Commerce Media (MCM) product
• You will be responsible for developing an ML-based online advertising platform for the rapidly growing retail media industry
• You will play a pivotal role building and developing our enterprise-ready solution. We’ve determined clear market fit and are now seeking senior and staff engineers to refine the MCM product
• You will lead feature development, design, optimization, testing, and maintenance of software applications and solutions for internal and external end users
• You will mentor others on the team and have the opportunity to lead high-impact projects

The Opportunity:

• Design and ship agentic software that helps advertisers manage campaigns through natural language interfaces and intelligent automation
• Build customer-facing applications that combine LLM capabilities with robust backend systems—from conversational campaign creation to AI-assisted performance insights
• Own the full stack: React/TypeScript frontends, Go/Python/Java services, and the infrastructure that connects them
• Collaborate closely with PM, data science, and partner teams to shape product direction and turn ambiguous goals into shipped features
• Operate what you build: dashboards, alerts, runbooks, and a sustainable on-call rotation
• Mentor engineers through code reviews, pairing, and design discussions
• Prototype and explore what's next—advanced analytics, creative-level reporting, and AI capabilities we haven't imagined yet

How Do I Know if the Role is Right For Me?

• 5+ years of software engineering experience
• Full-stack development experience—you're comfortable across the frontend, backend, and the glue in between
• Hands-on experience building LLM-based applications (agents, tool use, prompt engineering, or similar)
• System design and development skills; from gathering requirements to design to implementation to production
• Experience in Cloud/Big Data platforms (e.g., AWS, GCE, GCP, Beam, Spark, BigTable, BigQuery etc.)
• Programming fundamentals, testing, and common algorithms and structures
• Track record of shipping customer-facing products
• Growth mindset—you stay current on emerging technologies and enjoy sharing knowledge with others
• Excellent communication and collaboration skills

Company Overview

ID.me is the next-generation digital identity wallet that simplifies how individuals securely prove their identity online. Consumers can verify their identity with ID.me once and seamlessly log in across websites without needing to create a new login and re-verify. Over 140 million users experience streamlined login and identity verification with ID.me at 20 federal agencies, 44 state government agencies, and 66 healthcare organizations. More than 600 consumer brands use ID.me to verify communities and user segments to honor service and build more authentic relationships. ID.me’s technology meets the federal standards for consumer authentication set by the Commerce Department and is approved as a NIST 800-63-3 IAL2 / AAL2 credential service provider by the Kantara Initiative. ID.me is committed to “No Identity Left Behind” to enable all people to have a secure digital identity. To learn more, visit https://network.id.me.

Role Overview

ID.me is seeking a Staff Data Engineer (SDE-V) to lead the design, build, and operation of the core data infrastructure that underpins our identity platform. This engineer will be responsible for ensuring the reliability, scalability, and performance of the systems that move, process, and store data across the company.

In this role, you’ll own and operate key data infrastructure components — including event streaming platforms, relational databases, and batch processing systems — while driving automation and engineering best practices that improve data platform reliability and developer efficiency. You’ll partner closely with Platform Engineering, Site Reliability Engineering, and Compliance teams to ensure ID.me’s data ecosystem meets demanding operational, security, and regulatory requirements.

This is a hands-on technical leadership role for a data infrastructure engineer who thrives at the intersection of distributed systems, platform engineering, and data operations.

This role is based out of our Mountain View, CA or McLean, VA offices and requires full-time in-office attendance.

Responsibilities

• Own and operate core data infrastructure, including event streaming, relational database, and batch processing platforms.
• Design and implement highly reliable, observable, and scalable data systems that enable real-time and batch data processing.
• Develop automation and guardrails for data governance, retention, and compliance, ensuring auditability and consistency across services.
• Partner with application, platform, and SRE teams to improve data access patterns, reliability SLAs, and recovery processes.
• Establish standards for data infrastructure monitoring, alerting, and capacity planning, ensuring proactive issue detection.
• Drive operational excellence by improving resilience, reducing toil, and implementing self-healing or automated recovery mechanisms.
• Evolve and optimize data pipelines that support downstream analytics, identity verification, and machine learning systems.
• Evaluate, implement, and operate event-driven and batch data platforms such as Kafka, Google Pub/Sub, Dataflow, or Temporal.
• Lead incident response and root cause analysis for production data systems, contributing to postmortems and platform improvements.
• Mentor engineers and advocate for reliability-focused engineering culture across teams.
• Data lake architecture — Design and build the data lake storage and compute topology (object storage, partitioning, lifecycle, tiering) to support batch and streaming workloads.

Minimum Qualifications

• Bachelor’s or Graduate degree in Computer Science, Software Engineering, or a related technical field.
• 8+ years of professional experience in data engineering, software engineering, or distributed systems development.
• 6+ years of programming experience in one or more languages such as Go, Python, or Java, with emphasis on automation and data system integration.

Preferred Qualifications

• Deep expertise in building and operating data systems—including relational databases, streaming, and batch platforms—in production environments.
• Hands-on experience administering and optimizing PostgreSQL or other relational databases in the cloud (AWS RDS, CloudSQL, or AlloyDB).
• Solid understanding of reliability engineering principles, including observability, SLOs, capacity management, and operational readiness.
• Experience managing cloud infrastructure (AWS or GCP) using infrastructure-as-code tools like Terraform, Kubernetes, or Helm.
• Experience operating event streaming platforms such as Kafka or Google Pub/Sub.
• Experience with batch and stream processing systems, including Dataflow, Temporal, or Airflow.
• Strong knowledge of data pipeline orchestration, change data capture, and schema management.
• Background in automation, incident response, and data platform observability.
• Familiarity with data governance and regulatory compliance frameworks (e.g., FedRAMP, GDPR, NIST).
• Contributions to open-source data infrastructure projects or strong community engagement in the data reliability space.
• Passion for performance engineering, system design, and mentoring others to deliver operational excellence at scale.
• AI-assisted development — Demonstrable experience using AI developer tools (e.g., code generation, test generation, query synthesis) to accelerate platform automation while validating outputs through code review and tests.
• Data-aware LLM usage — Ability to safely use large language models for tasks such as SQL generation, data lineage summarization, and runbook drafting while ensuring no sensitive data is exposed to external models and all prompts and outputs are logged for audit.

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.

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

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

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/.

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#LI-Hybrid

P24712_3413650

P24715_3413656

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.

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PID: P24412_3380938

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)

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P23578_3268067

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

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

Anduril is developing and deploying an integrated system to make UxVs highly effective through the entire mission lifecycle. From fleet management, to mission planning, live execution, and integrations into other DOD systems, Lattice is enabling the military to fight at scale with robots across all domains. Anduril is leveraging AI across all aspects of this lifecycle to reduce the barrier to entry for new operators, and increase the scale at which operators can leverage Lattice.

Your Job is to design, implement, and evolve the means by which Agents interact with classical software systems. You will contribute to test and eval infrastructure, deployment software, agent tool calling, prompt engineering, and other agent techniques in order to achieve best-in-class performance with frontier and edge deployed models. You will increase the performance and quality of agentic interaction patterns, and you will expand the surface area by which Agents can interact with the overall Lattice system. - good to ship

Required Qualifications

• Demonstrated deep knowledge of the implementation and use of LLM’s
• Experience integrating agents into classical systems 
• Strong programming skills in Python or other core languages (Java, Go etc)
• PhD or Master’s degree in Computer Science, Robotics, Machine Learning, or a related field, or equivalent practical experience.

Preferred Qualifications

• Experience with simulation or real-world validation for autonomous vehicles is highly desirable
• Novel application track record and experience including first author publications, participation in peer reviewed conferences, contribution to open source projects, and demonstrated contribution to the ML and AI community.
• Experience in multi-modal sensor data processing (e.g., cameras, LiDAR, radar).
• Familiarity with ML Ops best practices, including model versioning and reproducible research pipelines.
• Familiarity with C/C++ is a plus.
• General software engineering experience solving motion planning or related robotics problems.

We are seeking a Generative AI Chief Engineer Lead to drive innovations in autonomous vehicle technology using deep learning and reinforcement learning. In this dynamic role, you will design state-of-the-art algorithms and systems that enable safe, efficient, and intelligent autonomous capabilities. Today, employing mass quantities of autonomous robots requires heavy human oversight and execution. Anduril is leveraging AI approaches to improve effectiveness of autonomous missions, offload operator burden, and speed up execution via realtime monitoring, recommendations to users, and multi-modal interaction patterns. You will apply proven and un-proven approaches to create prototypes for expanding the capability of autonomous systems.

What You’ll Do

• Develop Advanced Agentic Software - Design and implement novel agent-based software systems to improve sensor perception, prediction, and decision-making for autonomous vehicles
• Apply Agentic Reasoning - Design and implement integrated agents and AI models to solve for end-user autonomous systems workflows.
• End-to-End System Integration - Collaborate with cross-functional teams to integrate research prototypes into robust, production-ready systems including simulation environments and real-world platforms.
• Research & Experimentation - Conduct research into reinforcement learning strategies and deep architectures, iterate on experimental designs, and evaluate performance using rigorous quantitative metrics.
• Data-Driven Innovation - Utilize real-world and synthetic data to enhance model robustness and generalization, leveraging scalable training pipelines on distributed systems.

Required Qualifications

• Sophisticated knowledge of LLM's with an understanding of how they work and how they're applied
• Solid experience with reinforcement learning methods and their application to autonomous systems.
• Proven experience of shipping products end to end
• Experience with simulation or real-world validation for autonomous vehicles is highly desirable.
• A degree in Computer Science, Robotics, Machine Learning, or a related field, or equivalent practical experience
• Eligible to obtain and maintain an active U.S. Top Secret security clearance
• Travel up to 40+% of time to build, test, and deploy capabilities in the real world

Preferred Qualifications

• PhD or Master’s degree in Computer Science, Robotics, Machine Learning, or a related field, or equivalent practical experience
• Novel application track record and experience including first author publications, participation in peer reviewed conferences, contribution to open source projects, and demonstrated contribution to the ML and AI community.
• Proven experience in deep learning research and development, particularly in generative AI. This includes diffusion models and autoregressive generative models.
• Experience in multi-modal sensor data processing (e.g., cameras, LiDAR, radar).
• Familiarity with ML Ops best practices, including model versioning and reproducible research pipelines.
• Strong programming skills in Python and familiarity with C/C++ is a plus.
• General software engineering experience solving motion planning or related robotics problems.

ABOUT THE TEAM:

The Developer Platform team builds the tools and infrastructure that power software development at Anduril. We own the company's primary developer CLI (2,300+ engineers, 93k+ invocations), CI/CD pipelines serving 3,500+ engineers across 23 product lines in the US, Australia, and UK, deployment and release management systems, and Anduril's LLM adoption platform. We are standing up a new agentic development initiative to build the next generation of AI-powered developer infrastructure. The team is growing fast and this is a ground-floor opportunity to define what agentic software development looks like at a company building mission-critical defense systems.

WHAT YOU'LL DO:

• Build multi-agent orchestration infrastructure that moves AI coding agents from individual developer machines to servers executing work autonomously across repositories at company scale
• Design and implement an agent-optimized, real-time knowledge base that gives AI agents deep context on codebases, architecture, and operational patterns
• Build a skills and plugin platform that lets any team encode their domain knowledge into reusable AI capabilities
• Improve CI/CD reliability and developer experience across 23 product lines
• Create release tooling that simplifies shipping software to production environments and robotic platforms
• Operate and evolve Anduril's LLM adoption platform: model rollouts, capacity management, cost attribution, and developer onboarding

REQUIRED QUALIFICATIONS:

• Strong software engineering fundamentals in one or more of: Go, Python, TypeScript
• An entrepreneur, builder, PM, and designer rolled into one. We need people with outstanding software taste who can identify the right problem, design the solution, build it, and ship it in days, not quarters.
• A passion for developer tooling. You notice friction in your own workflow and cannot help but fix it. You spend 4 hours sharpening the axe and 30 minutes chopping wood.
• Demonstrated ability to quickly learn and adapt to unfamiliar technologies across multiple domains
• Must be a U.S. Person due to required access to U.S. export controlled information or facilities

PREFERRED QUALIFICATIONS:

• Experience building developer tools, CLIs, CI/CD systems, or platform infrastructure
• Experience with Kubernetes, Nix, or cloud infrastructure (AWS/Azure)
• Genuine interest in LLMs and agentic systems as applied to developer productivity. If you are already building with AI coding agents in your daily workflow, you will feel right at home.
• Prior work on LLM integrations, prompt engineering, or agent frameworks

Anduril is developing and deploying an integrated system to make UxVs highly effective through the entire mission lifecycle. From fleet management, to mission planning, live execution, and integrations into other DOD systems, Lattice is enabling the military to fight at scale with robots across all domains. Anduril is leveraging AI across all aspects of this lifecycle to reduce the barrier to entry for new operators, and increase the scale at which operators can leverage Lattice.

Your Job is to design, implement, and evolve the means by which Agents interact with classical software systems. You will contribute to test and eval infrastructure, deployment software, agent tool calling, prompt engineering, and other agent techniques in order to achieve best-in-class performance with frontier and edge deployed models. You will increase the performance and quality of agentic interaction patterns, and you will expand the surface area by which Agents can interact with the overall Lattice system. - good to ship

Required Qualifications

• Demonstrated deep knowledge of the implementation and use of LLM’s
• Experience integrating agents into classical systems 
• Strong programming skills in Python or other core languages (Java, Go etc)
• PhD or Master’s degree in Computer Science, Robotics, Machine Learning, or a related field, or equivalent practical experience.

Preferred Qualifications

• Experience with simulation or real-world validation for autonomous vehicles is highly desirable
• Novel application track record and experience including first author publications, participation in peer reviewed conferences, contribution to open source projects, and demonstrated contribution to the ML and AI community.
• Experience in multi-modal sensor data processing (e.g., cameras, LiDAR, radar).
• Familiarity with ML Ops best practices, including model versioning and reproducible research pipelines.
• Familiarity with C/C++ is a plus.
• General software engineering experience solving motion planning or related robotics problems.

We are seeking a AI Chief Engineering Lead to drive innovations in autonomous vehicle technology using deep learning and reinforcement learning. In this dynamic role, you will design state-of-the-art algorithms and systems that enable safe, efficient, and intelligent autonomous capabilities. Today, employing mass quantities of autonomous robots requires heavy human oversight and execution. Anduril is leveraging AI approaches to improve effectiveness of autonomous missions, offload operator burden, and speed up execution via realtime monitoring, recommendations to users, and multi-modal interaction patterns. You will apply proven and un-proven approaches to create prototypes for expanding the capability of autonomous systems.

What You’ll Do

• Develop Advanced Agentic Software - Design and implement novel agent-based software systems to improve sensor perception, prediction, and decision-making for autonomous vehicles
• Apply Agentic Reasoning - Design and implement integrated agents and AI models to solve for end-user autonomous systems workflows.
• End-to-End System Integration - Collaborate with cross-functional teams to integrate research prototypes into robust, production-ready systems including simulation environments and real-world platforms.
• Research & Experimentation - Conduct research into reinforcement learning strategies and deep architectures, iterate on experimental designs, and evaluate performance using rigorous quantitative metrics.
• Data-Driven Innovation - Utilize real-world and synthetic data to enhance model robustness and generalization, leveraging scalable training pipelines on distributed systems.

Required Qualifications

• Sophisticated knowledge of LLM's with an understanding of how they work and how they're applied
• Solid experience with reinforcement learning methods and their application to autonomous systems.
• Proven experience of shipping products end to end
• Experience with simulation or real-world validation for autonomous vehicles is highly desirable.
• A degree in Computer Science, Robotics, Machine Learning, or a related field, or equivalent practical experience
• Eligible to obtain and maintain an active U.S. Top Secret security clearance
• Travel up to 40+% of time to build, test, and deploy capabilities in the real world

Preferred Qualifications

• PhD or Master’s degree in Computer Science, Robotics, Machine Learning, or a related field, or equivalent practical experience
• Novel application track record and experience including first author publications, participation in peer reviewed conferences, contribution to open source projects, and demonstrated contribution to the ML and AI community.
• Proven experience in deep learning research and development, particularly in generative AI. This includes diffusion models and autoregressive generative models.
• Experience in multi-modal sensor data processing (e.g., cameras, LiDAR, radar).
• Familiarity with ML Ops best practices, including model versioning and reproducible research pipelines.
• Strong programming skills in Python and familiarity with C/C++ is a plus.

Sendbird is on a mission to build the AI workforce of tomorrow. For over a decade, we built the infrastructure behind conversations—chat, voice, video, messaging APIs—and became the #1 CPaaS platform for in-app communications. 4,000+ brands trust us. 7 billion messages flow through our platform every month. 300 million monthly active users.

We powered conversations for DoorDash, Match Group, Noom, Yahoo Sports, Rakuten, and thousands of others. We were good at what we did. Really good.

We also saw it early: AI would fundamentally reshape how businesses talk to customers. The infrastructure we'd spent a decade building would become commoditized. The value would move up the stack—into intelligence, into experience, into outcomes.

We had a choice: protect what we built, or reinvent ourselves.

We chose reinvention.

In December 2024, we made the full strategic pivot to AI-first customer experience. By February 2025, we'd launched our AI agent for enterprise CX—built on a decade of conversation data, now with intelligence on top. And in November 2025, we rebranded to Delight.ai.

The name says it all. AI's real promise isn't efficiency or cost savings. It's giving customers back something they lost—the feeling of being truly understood and cared for. Not satisfied. Delighted.

Delight.ai is the AI concierge for customer experience. Most AI agents forget you the moment the conversation ends. Ours doesn't. Delight.ai builds memory over time, learns preferences, and connects context across every channel—chat, SMS, email, voice, WhatsApp—without losing the thread. We're building AI that makes customers feel understood, seen, and remembered.

About the Role

Most marketing teams are bolting AI onto a content process built for 2018. We're building one for 2026. 

The first is to produce excellent content and drive organic growth. You're an SEO expert across keyword research, on-page, technical, content clusters, and measurement, and you're hungry to figure out GEO, because nobody's a GEO expert yet and the playbook is being written in real time. Own the strategy and the execution that make Delight.ai discoverable wherever buyers and LLMs research: Google, Perplexity, ChatGPT, Claude, Reddit, the podcast feeds CX leaders actually listen to. SEO and GEO aren't checklists you run after the writing is done. They shape what gets written and how. The output is long-form posts, narratives, technical explainers, podcast prep, the occasional Reddit thread that earns its own citation. The bar is high. Your work has to hold up in front of CX leaders running real programs at airlines, retailers, and B2B SaaS companies, and in front of our own product and engineering teams. Sloppy generalities won't survive either audience, and they won't earn citations either.

The second is to build the engine that lets a small team produce work like that at volume. Pipelines, agents, prompt libraries, retrieval layers, schemas, design systems. The connective tissue that turns one writer into a content function. Delight.ai is an AI concierge platform, and our marketing should look like it was made by people who actually believe in the technology they sell. We have the tokens. Use them.

You will join a small, high-agency team at the intersection of product, marketing, and web. We publish for a world where buyers and LLMs decide who gets considered before a sales conversation ever happens — and we're building Delight.ai for that same world. This role reports to the Head of Product Marketing.

If you've built systems like this before, or you're excited to, you'll have a lot of room to shape the approach.

When applying, please submit one content sample (blog post or other long-form piece) that you feel expresses your ability to excel at this role. 

How We Work

Content is an engineering discipline here. We hold quality bars, build reusable components, and design systems that let us iterate fast. The best people on this team have mastered the craft by hand. They can write a great post from a blank page, and they use AI to multiply what one person can ship.

You'll work in a stack that may include Claude, Claude Code, and other LLM-native tools for research, and building the agents that orchestrate our content workflows end-to-end. Some of the best workflows on our team started as someone's side project.

If you've built systems like this before, or you're hungry to, you'll have real room to shape the approach.

What You Will Do

• Ship excellent content. Posts, narratives, and explainers about Delight.ai's AI concierge platform, our memory and personalization, omnichannel, and Trust OS pillars, and the CX workflows they unlock. Long-form is the core, but the engine reaches into podcast prep and pitching, Reddit and community participation, and wherever else buyers and LLMs go to form opinions.
• Build the content engine that helps the team move faster and stay sharper:
• Create repeatable, AI-augmented pipelines for drafting, expert review, publishing, and updates
• Build agents and workflows that support the content development process end-to-end
• Design the AEO/GEO foundation — schema, structured outlines, citation-ready formats — that makes Delight.ai discoverable across Google, Perplexity, ChatGPT, Claude, and whatever comes next
• Be customer zero. Use our agents, our flows, our dashboards. Find what's confusing. Push on what doesn't hold up. Your content will read like you've actually deployed AI concierge agents because you have.
• Stay close to the market. Our product, the CX industry, and the way buyers and the models that serve them evaluate vendors are all moving fast. Keep up.
• Close the loop. Track what's working from content to traffic to pipeline across every surface, including which podcast appearances and community conversations actually move pipeline. Learn what humans and models pick up. Iterate.

About You

• 5+ years writing long-form for a living in content marketing, technical writing, developer advocacy, or something close. Show us work that moved something: pipeline, perception, search rankings, or all three.
• Deep SEO expertise. Years of doing the work: keyword research, technical SEO, on-page, content strategy, measurement. You can spec a content cluster, audit a site, and explain why a page isn't ranking without opening a single tool.
• Curious and opinionated about GEO. Nobody's an expert yet. You've been paying attention, you have early hypotheses about what works, and you want to be one of the people who figures it out. Not someone who waits for a best-practices guide to drop.
• Hands-on with AI tools, agents, or automation. You've deployed things, not just written about them, and you can talk through the tradeoffs you made.
• You can collaborate deeply with product and engineering, ask sharp questions, and earn trust through accuracy
• You learn quickly and can turn new domains (a new vertical, a new product capability, a new channel) into clear, comprehensive explanations
• You thrive in a fast-paced environment with high agency and strong ownership
• You have strong opinions about which AI tools work best for what, and a library of custom prompts to back them up

What we offer:

We take care of the people who build the future. Here's some of what you can expect when you join Sendbird:

• Medical, dental, and vision coverage, on us. Sendbird covers 100% of the premium for our employees and roughly 80% for their dependents.
• Generous time off. 20 days PTO, 13 company holidays, 7 sick days, 2 rest & rejuvenation days, 1 volunteer day, and your birthday off.
• $3,500 annual "Be Your Best Self" boost. Spend it on anything that helps you grow. Gym memberships, therapy, books, courses, massages, and more.
• Parental leave for all new parents. Time to be present for the moments that matter most.
• 401(k) from day one. Auto-enrollment, flexible contributions, and access to Vanguard's investment platform.
• HSA & FSA options. Pre-tax accounts to cover healthcare, dependent care, and commuter expenses.
• Life & disability coverage, fully paid. Life insurance and AD&D at 2x your salary, plus short- and long-term disability at no cost to you.

Pay Transparency

For cash compensation, we set standard ranges for all roles based on function, level, and geographic location. To determine our ranges, we utilize a variety of compensation data benchmarked against similar-stage growth companies. A reasonable estimate of the current salary range for this role is $145,000.00 – $170,000.00. This range is specific to the San Francisco Bay market. We consider several factors when making final compensation decisions including, but not limited to, skill sets, experience and training, licensure and certifications, and other business and organizational needs which may cause your specific offer to vary from the amount listed above.

Flexible Work Policy

We offer a flexible work schedule at Sendbird. We also value collaboration and relationship building. With those values in mind, we require all employees within an hour's commute range of their local office to gather with their team in the office three days per week as a minimum. Some of our roles require a more frequent in-office schedule. Please work with your manager to understand the office time requirements for your position.

What diversity and inclusion mean to us

There is no such thing as a perfect candidate and the best employees come from a wide range of backgrounds, experiences, and skill sets. Sendbird is a place where everyone can learn and grow. We respect, promote, and encourage diversity for equal employment opportunities and encourage you to apply if this role excites you.

Why Sendbird

We're not in maintenance mode. We're rebuilding how businesses connect with their customers using AI, and we're moving fast. If you want to own something real, build things that matter, and work at a company that has the infrastructure, the data, and the conviction to lead this shift, this is the place.

Sendbird is building the AI workforce of tomorrow, and we hire that way too. Learn more about our interview process, how we evaluate candidates, and the role AI plays along the way.

Purpose

The Enterprise Platform Application Specialist is responsible for aligning Microsoft’s evolving platform and capabilities with business outcomes. 
 

The Role

Platform Strategy & Governance  

• Serve as the strategic owner of the Microsoft 365 platform, aligning Microsoft’s roadmap with business priorities
• Define and maintain governance standards for Teams, SharePoint, OneDrive, and Exchange Online
• Evaluate new Microsoft features and lead enterprise readiness, risk assessment, and rollout planning  

Security, Identity & Compliance  

• Activate PIM for the Enterprise and work with the Team to better execute Role Based Access Control (RBAC)
• Partner with Security and Compliance teams to implement retention policies, sensitivity labeling, and audit capabilities
• Ensure M365 services align with regulatory, contractual, and organizational security requirements  

Adoption & Enablement  

• Lead adoption strategies for new productivity capabilities, including Microsoft Teams, Outlook and Copilot
• Use analytics and reporting to monitor usage, adoption, and value realization 
• Work with the A.I. team to enable inhouse LLM to work with documents within the M365 system 

Basic Qualifications

• Ability to lawfully access information and technology that is subject to US export controls 
• Qualified candidates should have a passion for technology, a business mindset, a customer service-oriented attitude, strong communication skills, and a willingness to work with others.
• The successful candidate will be able to prioritize, troubleshoot/resolve problems and follow-through with internal clients
• Minimum of 7 years of experience in Information Technology
• Minimum of 5 years as a hands-on administrator of Microsoft solutions, including Outlook, Office suite, Teams, SharePoint, and OneDrive, with at least 3 years in an environment with 500+ end users
• Minimum of 3 years of experience with Microsoft Active Directory and Entra ID
• Ability to understand basic Windows Active Directory; user accounts and security groups
• Strong communication, written, and customer service skills
• High aptitude and willingness to learn new technologies
• A self-starter that can work with minimal supervision; highly organized

Preferred Qualifications

• Experience in enterprise environments (500+ users preferred)
• PowerShell automation experience at scale
• Familiarity with Microsoft Purview, Defender for Office 365, Power Platform, and Microsoft Graph
• Microsoft certifications (M365, Identity) preferred

Work Environment

• Hybrid

Role Overview

As a Senior Staff Backend Engineer on the Platform Core team, you will build the services that power the platform foundation — the Entity Registry, change tracking, typed source system connectors, and the integration infrastructure that every application depends on. This role focuses on Go backend services, PostgreSQL performance, and building durable infrastructure that application teams program against through the Platform SDK.

Responsibilities

• Build and maintain core backend services (Go preferred)
• Build scalable systems that use a range of inter-process communication mechanisms (blackboard, direct, queues, etc.)
• Build common data models from diverse data sources
• Build APIs and SDKs that accelerate application development
• Design and optimize PostgreSQL schemas for performance and evolution
• Define and implement strongly typed reusable APIs (gRPC/protobuf or REST/OpenAPI)
• Develop entity CRUD, search, and traversal capabilities
• Implement change tracking and event propagation patterns (e.g., outbox pattern)
• Optimize database performance (indexing strategy, query planning, connection management)
• Implement middleware for authentication, authorization, rate limiting, and audit logging
• Contribute to observability, reliability, and CI/CD standards
• Collaborate with platform and application teams to validate services in production use cases
• Support AI-assisted workflows by exposing clean, structured APIs suitable for controlled automation
  
  

Required Qualifications

• 10+ years backend engineering experience
• Strong hands-on experience in Go (or equivalent backend experience with willingness to work in Go)
• Deep expertise with relational databases, ideally PostgreSQL, to include:
  • Schema design
  • Performance tuning
  • Indexing strategies
  • Query plan analysis
    
    
• Experience building and operating distributed systems
• Experience defining and implementing typed service contracts
• AWS or other cloud-native infrastructure experience
• Strong understanding of reliability patterns (idempotency, retries, consistency)
• Demonstrated experience defining and developing APIs and SDKs
  
  

Preferred Qualifications

• Experience building typed connectors or integration services against enterprise APIs (OData, REST, SCIM)
• Experience with JSONB modeling or complex relational traversal patterns
• Experience with gRPC and protobuf
• Experience with change data capture (CDC) or event streaming
• Experience implementing policy-as-code authorization (Cerbos, OPA, or similar)
• Kubernetes (EKS) and infrastructure-as-code (Terraform) familiarity
• Experience building services consumed by LLM pipelines or AI-assisted workflows

Please note that this job description is intended to provide a general overview of the position and does not include an exhaustive list of responsibilities and qualifications

At Archer we aim to attract, retain, and motivate talent that possess the skills and leadership necessary to grow our business. We drive a pay-for-performance culture and reward performance that supports the Company’s business strategy. For this position we are targeting a base pay between $182,500 - $220,000. Actual compensation offered will be determined by factors such as job-related knowledge, skills, and experience.

Role Overview

We are seeking a deeply technical, hands-on Principal Platform Architect and Tech Lead to serve as the technical authority for the Enterprise OS team. This high-leverage role is centered on building a foundational platform layer that sits above core enterprise systems (e.g., SAP S/4HANA, Workday, Google Workspace, Okta).

You will help establish foundational platform capabilities that streamline the development of secure, reliable applications atop unified enterprise data. This is a deeply technical, high-leverage role. You will not only design and build core services but also lead the engineering team in execution, set rigorous platform standards, and own the technical roadmap.

Key Responsibilities

• Technical Leadership: Act as the Tech Lead for the platform team. Drive technical decisions, manage architectural trade-offs, and ensure the team adheres to high engineering standards through rigorous design and code reviews.
• Platform Design Ownership: Define the canonical entity model, design the connector interface for typed Go services across source systems, and own the Platform SDK used by application teams.
• Core Service Development: Lead the development of services enabling policy-controlled access, traceability, and automation, including AI-assisted workflows with robust guardrails.
• Execution & Validation: Translate the platform vision into actionable engineering milestones. Your designs will be rapidly validated through production applications.

Responsibilities

• Define canonical entity models that normalize data across multiple enterprise systems (e.g., finance, supply chain, HR)
• Demonstrated ability to lead engineering teams through the full SDLC of complex platform products.
• Design and implement core backend services (Go preferred, Java experience also valued)
• Define strongly typed API contracts and versioning standards using protobuf, with the Platform SDK as the single interface applications build against
• Design a portable data architecture using PostgreSQL, including schema evolution and performance strategy
• Establish scalable connector/integration patterns for ingesting, enriching, and serving enterprise entities
• Build a policy-based authorization approach (RBAC with attribute-aware controls) with entity-level access control and data masking where needed
• Define event propagation patterns (e.g., outbox pattern) and a clear path to CDC/event streaming as the platform matures
• Establish auditability, traceability, and observability standards for platform services
• Enable AI-assisted workflows safely (e.g., classification/summarization/suggested actions) with strict access boundaries and full audit logs
• Mentor engineers and collaborate with application teams to validate the platform through real production use cases
  
  

Qualifications

• 15+ years building distributed systems, backend platforms, or internal developer platforms
• Strong hands-on backend engineering experience  (Go preferred)
• Deep expertise in relational databases, ideally PostgreSQL (schema design, indexing, performance tuning, migrations)
• Experience designing canonical data models across heterogeneous systems
• Experience defining durable API contracts and operating them over time (versioning, compatibility, reliability)
• Experience implementing secure authorization patterns (RBAC and fine-grained access controls)
• Experience designing event-driven systems and reliability patterns (idempotency, retries, consistency)
• Cloud-native experience (AWS/GCP preferred) and comfort working across infrastructure/application boundaries
• Demonstrated ability to ship production systems used by other teams

Preferred:

• Experience with typed contracts
• Experience with policy-as-code authorization (e.g., OPA/Cerbos or similar)
• Experience integrating enterprise identity providers (OIDC/SAML; Okta is a plus)
• Experience building internal SDKs/frameworks used by multiple teams
• Experience incorporating AI/LLM capabilities into production systems with strong governance (access boundaries, prompt-safety patterns, human-in-the-loop controls)
• Experience integrating with ERP/HR systems (SAP, Workday, etc.)
• Experience with enterprise data integration patterns: multi-table source joins, delta sync strategies, field-level provenance, canonical model design

Please note that this job description is intended to provide a general overview of the position and does not include an exhaustive list of responsibilities and qualifications

At Archer we aim to attract, retain, and motivate talent that possess the skills and leadership necessary to grow our business. We drive a pay-for-performance culture and reward performance that supports the Company’s business strategy. For this position we are targeting a base pay between 219,000 - 265,000. Actual compensation offered will be determined by factors such as job-related knowledge, skills, and experience.

About the Role

As our Staff AI Developer Relations Engineer, you’ll be the face of You.com to our developer community, and own developer audience growth, social influence, and technical content. Your goal will be to amplify You.com’s presence in the AI community by creating high-impact code, content, and forging relationships with the developer community.

Responsibilities

• Create high-quality code, content, use cases, and documentation on You.com portfolio of search apis, and emerging AI trends and broadcast it to community via social  
• Increase audience awareness of You.com by contributing to popular repos and evangelising You.com to influential developers / frameworks
• Host & participate in livestreams, workshops, conferences, and AMAs
• Actively follow and participate in the conversation on emerging AI topics on social and drive visibility to You.com by engaging with developer community
• Build demo repos and example workflows to inspire the developer community
• Collaborate with other creators to expand reach and engagement

Qualifications

• Strong presence on GitHub, YouTube, LinkedIn, X, or other platforms
• Proven track record on engaging with developer community
• Experience speaking at conferences or leading workshops
• Passion for shaping developer adoption and engagement
• Hands on developer experience
• Experience growing newsletters, social channels, or communities
• Data-driven approach to content strategy and distribution
• 50K+ followers across developer or AI-focused platforms is a plus
• Experience running influencer programs or creator partnerships is a plus

Position Overview:

As the Director of Monetization Strategy, you will be the primary architect of Iterable’s economic engine. You aren't just managing a price list; you are defining how we capture value in a rapidly evolving MarTech ecosystem. You will sit at the intersection of Product, Sales, Finance, and Marketing to design and execute pricing and packaging strategies that drive sustainable growth, expand Net Revenue Retention (NRR), and align our success with our customers' success.

Responsibilities:

• • Strategic Vision: Lead the long-term monetization roadmap. You’ll evolve our current models from usage-based pricing toward value-based frameworks that reflect the power of our AI-driven orchestration.
  • Cross-Functional Leadership: Act as the "connective tissue" between Product (to price new features, and ensure our roadmap is optimized for capturing value), Marketing (to position value), and Sales (to ensure deal velocity).
  • Market Intelligence: Conduct deep-dive competitive analysis and buyer research to identify gaps in our current monetization strategy and capitalize on emerging market trends.
  • Packaging & Tiering: Design and optimize product bundles and editions that simplify the buying process for mid-market and enterprise customers alike.
  • Operational Excellence: Partner with RevOps to implement pricing changes within our systems (CPQ, billing) and develop the discounting frameworks and "guardrails" for the field.
  • Change Management: Lead the internal enablement for global sales teams, ensuring they can confidently articulate the "why" behind our pricing.

Qualifications:

• You have 10+ years of experience in SaaS monetization, management consulting, or strategic finance. You think in systems and understand the downstream impacts of a single pricing lever.
• You have direct experience in SaaS monetization, with a particular focus on monetizing AI
• You are comfortable navigating complex datasets to find the "signal" in the noise. You use data to prove your hypotheses about price elasticity and expansion paths.
• You can distill complex economic theories into simple, persuasive narratives for the Executive Leadership Team (ELT).
• You don't just want a seat at the table; you want to build the table. You enjoy creating processes where none existed.

Bonus Points

• Experience building and productionizing LLM based, agentic or autonomous systems that handle complex orchestration and evaluation.
• Experience establishing shared AI platforms or internal developer enablement capabilities
• Familiarity with analytics systems, experimentation workflows, or decisioning frameworks

Perks & Benefits:

• Paid parental leave
• Competitive salaries, meaningful equity, & 401(k) plan
• Medical, dental, vision, & life insurance
• Balance Days (additional paid holidays)
• Fertility & Adoption Assistance
• Paid Sabbatical
• Flexible PTO
• Monthly Employee Wellness allowance 
• Monthly Professional Development allowance 
• Pre-tax commuter benefits
• Complete laptop workstation

The US base salary range for this position at the start of employment is $172,000 - $260,000. Within this range, individual pay is determined by specific US work location, as well as additional factors, including job-related skills, experience, relevant education or training, and internal equity considerations.

Please note that the range listed above reflects only base salary. The total compensation package includes variable pay (where applicable), equity, plus a range of benefits, including medical, dental, vision, and financial. In addition, we offer perks such as generous stipends for health & fitness and learning & development, among others.

About Roofstock

What we do and why we do it

As the leading end-to-end investment platform for single-family rental homes (SFR), our mission is to reinvent the rental housing ecosystem for the benefit of all. We successfully merge our passion for helping investors build wealth through real estate with cutting edge technology that transforms the way they do it.

How it’s going (and growing)

With a talented team of 750+ Roofsters, our collaborative, can-do culture is what fuels our growth. In 2022, we closed on our Series E, raising $240 million, and have offices in the Bay Area and New York City. Our growth includes recent acquisitions of Stessa (financial and asset management software), RentPrep (tenant screening and placement service for landlords), and Mynd (property management platform for both Retail and Institutional investors). In 2025, Roofstock took an ownership stake in Casago (short-term rental management services), expanding our platform to support both long-term and short-term rental investment services.

About the Role

As a Senior AI Product Manager on Roofstock’s Property Management team, you will own and execute key product initiatives across internal tools and customer-facing experiences for investors, residents, and vendors. This is a hands-on individual contributor role focused on driving execution, shaping roadmap priorities, and delivering scalable solutions that improve efficiency and user experience. You’ll partner closely with engineering, design, operations, and data teams to bring impactful products to life. We’re looking for a strong product executor with experience in consumer software, SaaS, proptech, or operational platforms who can translate complex business needs into intuitive solutions, leverage data to inform decisions, and identify opportunities to incorporate AI and automation into workflows.

Responsibilities

Product Ownership & Execution

• Own and drive specific product areas within the property management platform from ideation through launch and iteration
• Translate business objectives into clear product requirements, user stories, and prioritized backlogs
• Partner with engineering and design teams to deliver high-quality, scalable product solutions
• Define and track key performance metrics to measure product success and drive continuous improvement
• Prioritize product features based on business impact, technical feasibility, and user needs

AI & Automation Integration

• Identify opportunities to apply agentic AI and automation to improve operational efficiency and reduce manual processes
• Partner with engineering and data teams to integrate AI-powered features (e.g., workflow automation, predictive insights, LLM-enabled tools)
• Contribute to a data-informed product approach by leveraging insights to enhance product functionality and user experience
• Stay informed on emerging AI technologies and evaluate practical applications within property management workflows

Cross-Functional Collaboration

• Work closely with operations teams to understand user needs, pain points, and opportunities for improvement
• Collaborate with stakeholders across engineering, design, and business teams to align on priorities and deliver outcomes
• Partner with go-to-market teams to support the successful rollout of new features and enhancements
• Engage with customers and users (investors, residents, vendors) to gather insights that inform product decisions

Continuous Improvement & Delivery

• Gather and incorporate user feedback to iterate on product features and improve overall experience
• Use data and analytics to inform decision-making and prioritize product enhancements
• Balance speed and quality in a fast-paced, evolving environment
• Contribute to scalable product development processes that support ongoing 

Qualifications

• 5 - 8+ years of product management experience
• Proven track record of delivering and iterating on technology products that drive business impact
• Experience working closely with cross-functional teams including engineering, design, and operations
• Exposure to AI/ML, automation tools, or data-driven product
• Data-driven mindset with the ability to define metrics and use insights to inform decisions

• Ability to break down complex problems into simple, scalable product solutions
• Excellent communication skills with the ability to collaborate across teams and influence stakeholders
• Experience building AI-powered products (e.g., large language models, agentic AI automation) and familiar with their practical applications and shortcomings
• Understanding of user experience principles and product analytics

Education

Bachelor’s degree in Computer Science, Business, or equivalent experience

Nice-to-haves

• Experience in real estate, property management, or proptech
• Experience working on internal tools or operational platforms
• Background in a high-growth or startup environment

Location

Bay Area / Oakland, CA

This position is classified as HYBRID within the Greater Oakland Area, with an expectation to be in-office on Tuesdays and Thursdays weekly.

Compensation

$175,000 - $205,000 on annual base salary. The compensation range may be adjusted based on experience and location.

Pay Transparency

Our compensation reflects several US geographic markets. The base pay for this position represents the expected salary for this position. Ultimately, in determining your pay it will be based on several factors including location, job-related knowledge, skills, experience and other job related factors.  Roofstock is a total compensation company; the base salary is only a part of our total compensation package.

Competitive & Unique Benefits Package

• Generous PTO Policy
• 13 Paid Holidays
• Volunteer Time Off
• Paid Parental Leave
• 401k Program
• Wellness and home office/cell phone subsidies
• Robust health, dental, vision insurance, and more

Must be authorized to work in the U.S. is a precondition of employment and we are unable to sponsor H1-B Visas at this time.

Any offer of employment is conditioned upon the successful completion of a background investigation.  

Commitment to Equal Employment Opportunity 

The company provides equal opportunity in all of our employment practices to all qualified employees and applicants without regard to race, color, religion, sex, gender, gender expression, gender identity, national origin, ancestry, citizenship, age, physical or mental disability, marital status, sexual orientation, military or veteran status, genetic information or any other category protected by federal, state and local laws. This policy applies to all aspects of the employment relationship, including recruitment, hiring, compensation, promotion, transfer, disciplinary action, layoff, return from layoff, training and social, and recreational programs. All such employment decisions will be made without unlawfully discriminating on any prohibited basis.

#LI-ONSITE

About the Role

We're seeking an exceptional Senior Engineering Leader to build and lead a high-performing engineering team focused on design and development of a distributed multi-tenant AI inference SaaS platform. Platform development responsibilities include but are not limited to software design, development and testing for multiple domains such as inference engines (AI/ML, program and compiler analysis), core platform services, and observability. This role sits at the intersection of systems engineering, AI/ML operations, and product development, requiring both deep technical expertise and proven leadership capabilities.

As a leader at Gruve, you'll drive the technical vision and execution of critical infrastructure that enables our AI capabilities at scale. You'll work closely with cross-functional partners including research scientists, product managers, and other engineering leaders to deliver robust, performant systems that power our AI products.

This position is based in the United States and reports to the SVP of Inferencing and Infrastructure Management

Key Responsibilities

• Team Leadership & Development: Build, mentor, and scale a world-class engineering team of 10-15+ engineers. Foster a culture of technical
• Excellence, collaboration, and continuous learning. Conduct performance reviews, career development planning, and succession planning.
• Technical Strategy & Architecture: Define and execute the technical roadmap for AI inference infrastructure, AI toolchains, and AI software development. Make critical architectural decisions that balance performance, scalability, maintainability, and cost.
• Compiler Design & Optimization: Lead the development of AI inference systems and optimizations for AI workloads, including graph optimization, kernel fusion, and hardware-specific code generation to maximize inference performance.
• AI Model Development & Deployment: Oversee the end-to-end lifecycle of AI models from development through production deployment, including model fine-tuning, quantization, distillation, and serving infrastructure.
• Inference API & Platform Development: Drive the design and implementation of scalable, low-latency inference APIs and platforms that serve models reliably at production scale with strict SLA requirements.
• Spec-Driven Development: Champion rigorous engineering practices including comprehensive technical specifications, design reviews, and documentation to ensure alignment and quality across complex projects.
• Cross-Functional Collaboration: Partner effectively with research, product, and business stakeholders to translate requirements into technical solutions and communicate progress, trade-offs, and risks clearly.
• Delivery & Execution: Own quarterly planning, roadmap prioritization, and on-time delivery of major initiatives. Establish metrics and KPIs to measure team performance and system health.

Basic Qualifications

• 10-15+ years of software engineering experience with at least 5+ years in engineering leadership roles managing teams of 5+ engineers
• Proven track record of building and scaling high-performing engineering teams in high-growth technology companies
• Deep expertise in systems programming languages (C++, Go, Rust, or similar) and architecture design
• Strong background in AI model design, optimization, or adjacent systems-level programming (LLVM, MLIR, XLA, or similar frameworks)
• Hands-on experience with AI/ML model development, training, and inference systems
• Experience with model fine-tuning techniques and deployment optimization (quantization, pruning, etc.)
• Demonstrated ability to design and build production-grade APIs and distributed systems
• Strong understanding of spec-driven development processes and engineering best practices · Excellent communication skills with ability to influence across all levels of the organization
• Demonstrated ability to work effectively with teams across multiple time zones
• Bachelor's degree in Computer Science, Engineering, or related technical field (or equivalent practical experience)

Preferred Qualifications

• Master's or PhD in Computer Science, Machine Learning, or related field
• Experience at leading AI/ML companies or research labs (OpenAI, Google DeepMind, Meta AI, Anthropic, etc.)
• Direct experience with modern ML frameworks (PyTorch, JAX, TensorFlow) and their compilation stacks
• Background in GPU programming (CUDA, Triton) and hardware acceleration for ML workloads
• Experience with transformer architectures and large language model (LLM) inference optimization
• Track record of shipping production ML systems serving millions of requests per day
• Contributions to open-source compiler or ML infrastructure projects
• Experience with cloud infrastructure (AWS, GCP, Azure) and containerization/orchestration (Kubernetes, Docker)
• Previous experience scaling teams from <10 to 20+ engineers

Salary Range 

$240,000 - $300,000 USD + Benefits

This position is with Gruve and is an on-site role based at the Gruve headquarters in Redwood City, California.

‍

Role 

We are looking for a seasoned Senior Tax Manager to join our Tax department. This role is based in our San Jose, CA headquarters (in office Tuesday-Thursday) or remotely across the US, reporting to the Senior Director, Tax. You will be responsible for leading Zscaler's North America income tax compliance process along with supporting the quarterly and annual global tax provision process. You will be heavily involved in shaping the tax department’s tax compliance policies and processes, while supporting the business needs of a fast-growing company. This is an individual contributor role with oversight responsibilities for local and remote team members.

What you’ll do (Role Expectations)

• Prepare and review the US and Canada income tax compliance including the U.S. federal, state and local income tax returns and estimated taxes
• Prepare and review the monthly and quarterly U.S. indirect tax compliance including sales tax, use tax, gross receipts tax and property tax
• Manage the R&D tax credit and SRED credit studies with the support of external service providers
• Assist with the Company’s ASC 740 income tax provision for interim and annual income tax provisions, as reported in the Company’s SEC Form 10-K/10-Q filings
• Build cross functional relationships with the broader finance organization

Who You Are (Success Profile)

• You act like an owner. Your passion for the mission fuels your bias for action. You operate with integrity because you genuinely care about the outcome. You adapt to what’s needed, navigating seamlessly between high-level strategy and hands-on execution.
• You are a problem-solver. You seek out challenges because you are energized by finding solutions, knowing that solving the hard problems delivers the biggest impact.
• You thrive in ambiguity. You're comfortable building the path as you walk it. You thrive in a dynamic environment, seeing ambiguity not as a hindrance, but as the raw material to build something meaningful.
• You are a high-trust collaborator. You are ambitious for the team, not just yourself. You embrace our challenge culture by giving and receiving ongoing feedback—knowing that candor delivered with clarity and respect is the truest form of teamwork and the fastest way to earn trust.
• You champion simplicity. You are skilled at distilling complex problems, user needs, and technical concepts into clear, simple, and actionable plans. You are a precise communicator who brings clarity and focus to every interaction.

What We’re Looking for (Minimum Qualifications)

• 10+ years of related experience with a combination of Big 4 public accounting and SaaS or tech industry experience
• Bachelor’s degree in accounting or Finance; CPA license, Master’s degree or LLM preferred
• Extensive technical knowledge of U.S. federal and state income tax; strong familiarity with ASC 740 preferred
• Advanced Excel and strong analytical skills to conduct thorough tax research and solve complex problems
• Strong oral and written communication skills, with ability to communicate complex subject matter to leadership, peers and other levels in the company

What Will Make You Stand Out (Preferred Qualifications)

• Experience in a fast moving, high growth environment with ability to react quickly to unexpected challenges and opportunities
• Extremely organized and able to manage work requirements to meet reporting deadlines

#LI-Remote #LI-AT4

The Product Solutions Architecture (PSA) team acts as a technical multiplier across Datadog. PSAs are domain experts who partner with Field teams on complex customer use cases across pre- and post-sales engagements and scale their impact by producing reusable collateral, including reference architectures, technical guides, and enablement assets. By feeding real-world customer insights back to Datadog Product teams, PSAs help influence product roadmaps while accelerating adoption, usage, and long-term customer success.

Datadog’s LLM Observability product enables organizations to monitor, troubleshoot, and optimize large-scale LLM-powered applications with confidence, while meeting requirements around data privacy, compliance, and cost management. As a Product Solutions Architect, you will partner closely with Datadog customers and the LLM Observability product team to design architectures, implement best practices, and drive adoption of LLM observability across customer environments.

At Datadog, we place value in our office culture - the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.

What You’ll Do:

• Serve as the in-house subject matter expert for Datadog’s LLM Observability product
• Partner with Field teams to provide hands-on technical and architectural guidance to enterprise customers adopting LLM Observability
• Create high-impact technical collateral, including reference architectures, technical guides, cookbooks, and documentation to enable Field teams and the broader customer community
• Build proofs of concept and small-scale deployments to validate solutions and reproduce real-world customer environments
• Act as a trusted advisor to Product Management by delivering actionable feedback informed by real-world field experience

Who You Are: 

• You bring a strong software engineering foundation, with hands-on experience building and operating LLM-powered applications in production environments, and are comfortable diving deep into codebases to understand architectural decisions, tradeoffs, and implementation details
• You are familiar with distributed systems and core observability concepts, such as tracing, metrics, and logging, and can translate those patterns into the emerging LLM observability domain, including LLM spans, evaluations, and prompt templates
• You have experience with languages such as Python and/or JavaScript/TypeScript
• You are comfortable operating in rapidly evolving, ambiguous technical domains
• You build deep context across teams and translate it into reusable, scalable solutions
• You take ownership from problem definition through implementation and measurable outcomes
• You are highly detail-oriented, particularly when working on architectures and customer-facing technical assets
• You bring strong listening and consultative skills and are experienced supporting customers in high-pressure, complex situations
• Able to sit up to 4 hours, traveling to and from client sites 
• Able to travel via auto, train, or air up to 40% of the time 

Bonus Points:

• Successful track record with 5+ years experience working as an Architect or Consultant 
• Experience using Datadog and/or other observability tools in an SRE or DevOps capacity
• Experience with LLM application evaluation and testing frameworks

Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply.

Benefits and Growth: 

• Best-in-breed onboarding
• Generous global benefits
• Intra-departmental mentor and buddy program for in-house networking
• New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
• Continuous professional development, product training, and career pathing
• An inclusive company culture, able to join our Community Guilds and Inclusion Talks

Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.

Datadog is seeking a strategic and data-driven Principal, Growth Marketing Manager – SEO/GEO to lead our organic growth through content and off-page strategy. This role is centered on defining what content we create, where it lives, and how it drives discovery across both traditional search engines and emerging AI/LLM platforms. You will partner closely with Website Experience, Product Marketing, and Engineering to identify and execute on content opportunities that drive measurable traffic and pipeline impact, while relying on Web Experience for technical SEO execution. This is a senior individual contributor role for someone who wakes up thinking about content ecosystems, audience intent, and how to win in organic discovery at scale.

At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.

What You’ll Do:

• Own Datadog’s content-led SEO/GEO strategy, defining the topics, formats, and ecosystems that drive measurable growth in traffic and pipeline
• Identify and prioritize high-impact content opportunities across product areas, and influence cross-functional teams to bring that content to life
• Map and optimize Datadog’s presence across the full ecosystem of LLM-ingested content (e.g., YouTube, Reddit, review sites) to improve AI-driven discoverability
• Design and execute a comprehensive off-page strategy, including link acquisition, digital PR, and authority-building initiatives
• Partner closely with the Website Experience team, who own technical SEO, to ensure content is effectively surfaced, indexed, and performant
• Create and contribute to high-impact content (e.g., flagship pieces, new formats, or experimental channels), setting the standard for quality and SEO performance

Who You Are:

10+ years of SEO experience, ideally in a B2B or high-growth tech environment

• Proven track record of growing qualified organic traffic and visibility through content strategy, not just technical SEO improvements
• Highly analytical and comfortable working in large datasets (SQL skills a plus) to identify trends, diagnose performance shifts, and quantify opportunity
• Hands-on experience using enterprise SEO tools such as Conductor and Ahrefs to drive strategy
• Strong understanding and perspective of how traditional search is evolving
• Experience marketing to developers, DevOps engineers, IT operations, or security practitioners, including writing content, is strongly preferred

Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply.

Benefits and Growth: 

• Generous and competitive benefits package
• New hire stock equity (RSUs) and employee stock purchase plan
• Continuous career development and pathing opportunities 
• Product training to develop an in-depth understanding of our product and space
• Best in breed onboarding
• Internal mentor and buddy program cross-departmentally
• Friendly and inclusive workplace culture

Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.

#LI-Hybrid

Shopmonkey's vision is to help every shop thrive by equipping them with the tools they need to run and grow their business. Our cloud based all-in-one shop management software takes owners and technicians from quote to cashing out a satisfied customer. Our software has a modern and intuitive UI and our backend is powered by the latest technologies so our clients can focus on the things they do best. As a Senior ML Engineer at Shopmonkey, you will be a part of a globally distributed engineering team working closely with your product and design counterparts. You will have the chance to work on the frontier of ML modeling, data pipelines, MLOps, and agentic AI systems to meet real-world auto shop needs. Shopmonkey has the structured data, workflows, and operational maturity to deliver ML powered systems that are not only intelligent but trusted and useful. You’ll move fast to bring ML systems from discovery all the way through production, helping to shape the future of the automotive care experience. For any Bay area based candidates, this would be hybrid with 2-3 days/week office at our Morgan Hill, CA office for collaboration. 

What you will do:

• Design, build, and ship production-ready ML models across a range of problem spaces: regression, classification, clustering, ranking, and recommendation systems.
• Conduct end-to-end development of ML systems: data gathering, experimentation, feature engineering, model training, evaluation, deployment, and monitoring.
• Define and track model performance metrics, run A/B tests, and iterate based on real-world feedback.
• Help design and implement shared feature stores so that reusable features can serve multiple models consistently in both batch and real-time contexts.
• Work within a modern MLOps environment to ensure scalable and reliable deployment of models.
• Contribute to training infrastructure, model versioning, and CI/CD pipelines for ML workflows.
• Work closely with data scientists and data engineers to develop data driven solutions that are high impact for businesses.
• Translate complex ML workflows into digestible updates for cross-functional stakeholders.
• Contribute to backlog velocity by owning appropriate tickets and delivering high-impact work in a collaborative, fast-paced environment.
• Implement NLP and LLM-powered components for sentiment analysis, real-time conversation evaluation, and behavior optimization.
• Contribute to analytics and predictive features such as no-show prediction and sentiment dashboards.
• Help build and ship AI agents that help automate key auto-shop business processes.

We are looking for people who have:

• Minimum of 5+ years of industry experience in applied machine learning; advanced degrees (Master’s or PhD) may offset years of experience.
• Proven experience shipping models into production (not just proof-of-concepts or notebooks).
• Proficiency in Python; experience with ML frameworks like PyTorch or Tensorflow.
• Strong foundations in classical ML/DL. Including some of the following: regression, classification, clustering, ranking, feature engineering, model evaluation, and experimentation.
• Bachelor’s degree in a STEM field, or equivalent practical experience.
• Strong collaboration and communication skills—comfortable working with PMs, designers, engineers and other cross functional team members.

Nice to have:

Candidates should have some experience in one or more of the following areas.

• Understanding of MLOps principles: model versioning, orchestration, evaluation, monitoring, model serving, and CI/CD for ML. 
• Understanding of MLOps, and experience with modern tooling like MLFlow, DVC, Airflow, etc.
• Experience with LLMs and NLP frameworks (e.g., TensorFlow, Hugging Face, LangChain).
• Experience with/interest in LLM workflows and agentic workflows
• Cloud infrastructure experience, (e.g. GCP, AWS).
• Familiarity with vector databases (e.g. Pinecone, pgvector) and embedding-based retrieval or similarity search.
• Strong SQL skills for working with large-scale data.
• Experience designing or contributing to feature stores (e.g. Feast, VertexAI Feature Store, Tecton) for shared, reusable feature pipelines.