We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did we ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we’re collectively disrupting the multi-billion-dollar e-commerce industry from the ground up. We are one of the fastest-growing e-commerce companies that established an unparalleled reputation for being a dominant and reliable force in South Korean commerce.

We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. We are all entrepreneurs surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day.

Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world.

Role Overview

We are seeking a highly skilled Senior Staff Software Engineer with deep technical expertise in Security and a passion for building secure, reliable, and scalable systems. This role focuses on technical leadership, architecture, and hands-on development to ensure the security and resilience of our core platforms.

You will drive the security, quality, and reliability of backend systems while influencing architecture decisions, mentoring engineers, and partnering with product teams on strategic initiatives.

What You Will Do

• Architect and implement secure, scalable backend systems using Java (Spring Boot) and AWS cloud-native services.
• Lead technical design reviews, enforce security best practices, and ensure system reliability and performance.
• Develop and integrate security features such as authentication, authorization, and identity management (SSO, OIDC, RBAC/ABAC, SCIM).
• Design and implement API security patterns and API authorization at scale for microservices and service mesh environments.
• Embed Generative AI capabilities (e.g., embeddings, RAG, LLM APIs) into product workflows securely and responsibly.
• Write and review code, unblock complex technical challenges, and make critical architectural decisions.
• Champion secure SDLC practices, cryptography standards, and compliance requirements.
• Collaborate with cross-functional teams to define technical roadmaps and deliver mission-critical systems at scale.

Minimum Qualifications

• Bachelor’s degree in Computer Science or related technical field.
• 8 years of professional software development and security engineering experience.
• Proven experience designing and developing large-scale distributed systems.
• Strong knowledge of security architecture

Preferred Qualifications

• Recent hands-on experience (last 3–4 years) building secure, distributed systems at scale, with strong exposure to AI/ML development and hosting in production environments.
• Experience with cloud platforms (AWS, Azure, GCP) for identity, ML infrastructure, and secure deployment.
• Familiarity with Generative AI integration and responsible implementation of LLM-based workflows.
• Exposure to data security principles, including encryption, secure data pipelines, and compliance frameworks.
• Ability to influence technical direction and mentor engineers in security best practices.
• Proven track record of delivering mission-critical, scalable systems in production at enterprise scale.
• Expertise in Java, Spring Boot, and AWS architecture/services (EKS, S3, Lambda, RDS, IAM, KMS).
• 7+ years of solid experience with fundamental algorithms, system design, and large distributed systems.
• Deep experience in cryptography and PKI systems, including certificate management and secure key lifecycle
• 7+ years of coding experience, specifically in Java.
• Strong knowledge of security architecture, authentication/authorization, and cryptographic principles.
• Hands-on experience in building large-scale serving and data infrastructure.
• Experience with service-oriented architecture and web application/services development
• Practical experience in utilizing AWS (Amazon Web Services).
• Experience in designing and constructing machine learning-based applications and systems.
• Experience in leading cross-team system design and execution.

Pay & Benefits   

Our compensation reflects the cost of living across several US geographic markets. At Coupang, your base pay is one part of your total compensation. 

The base pay for this position ranges from $174,00/year to $299,000/year. Pay is based on several factors including market location and may vary depending on job-related knowledge, skills, and experience.

General Description of All Benefits  

• Medical/Dental/Vision/Life, AD&D insurance  
• Flexible Spending Accounts (FSA) & Health Savings Account (HSA)
• Long-term/Short-term Disability
• Employee Assistance Program (EAP) program
• 401K Plan with Company Match
• 18-21 days of the Paid Time Off (PTO) a year based on the tenure
• 12 Public Holidays
• Paid Parental leave
• Pre-tax commuter benefits
• MTV - [Free] Electric Car Charging Station 

General Description of Other Compensation

 “Other Compensation” includes, but is not limited to, bonuses, equity, or other forms of compensation that would be offered to the hired applicant in addition to their established salary range or wage scale.  

Recruitment Process

• Application Review - Phone Interview - Onsite (or Virtual Onsite) Interview – Offer
• The exact nature of the recruitment process may vary according to the specific job and may be changed due to scheduling or other circumstances.
• Interview schedules and the results will be informed to the applicant via the e-mail address submitted at the application stage.

Details to Consider

• This job posting may be closed prior to the stated end date for application if all openings are filled.
• Coupang has the right to rescind an offer of employment if a candidate is found to have submitted false information as part of the application process.
• Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws.

Privacy Notice

• Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below: https://www.coupang.jobs/privacy-policy/

Coupang is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, or gender (including pregnancy, gender identity, gender expression, sexual orientation, transgender status), national origin, age, disability, medical condition, HIV/AIDS or Hepatitis C status, marital status, military or veteran status, use of a trained dog guide or service animal, political activities, or affiliations, citizenship, or any other characteristic or class protected by the laws or regulations in the locations where we operate. If you need assistance and/or reasonable accommodation in the recruiting process due to a disability, please contact us at usrecruiting@coupang.com.

Job Requisition ID: R0067878

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

As Commercial Counsel primarily supporting Stripe’s Stablecoin & Crypto team, you will lead complex commercial and contractual negotiations, advise on product launches, and help scale Stripe’s legal and operational infrastructure. You will work closely with Sales, Product Legal, Partnerships, Risk, Tax, Operations, and external counsel to enable safe, compliant, and commercially sound growth of Stripe’s crypto, stablecoin, and wallet offerings.

We are committed to building an inclusive work environment where all Stripes feel welcomed as their authentic selves—inclusive of all genders, sexual orientations, ethnicities, races, education, ages, and other personal characteristics. We work on broadening our internal diversity because we want to be culturally equipped to build products and solutions for our diverse user base.

What you’ll do

Responsibilities

• Support the Sales team, with particular focus on Stripe’s Stablecoin & Crypto team, leading negotiations and advising on a wide range of commercial and legal issues
• Work closely with Product Legal to bring new products and features to market, including drafting service terms and providing contractual, commercial, and user-experience advice for launches
• Be an integral part of the build out of Stripe’s commercial legal infrastructure to enable scalable, efficient operations in line with Stripe’s growth. This includes advising on the contractual integration of services provided by Stripe’s cryptocurrency, stablecoin, and wallet infrastructure acquisitions (including Bridge and Privy), drafting and maintaining agreements and playbooks, and leading or contributing to projects that improve internal processes and operational efficiencies, including by leveraging AI tooling
• Partner with teams across Stripe, including Sales, Partnerships, Operations, Product, Tax, and Risk groups, to align legal solutions with business priorities
• Serve as a proactive and strategic business partner to senior managers and act as a trusted advisor on commercial strategy and risk
• Develop and deliver training, playbooks, and other resources to help the Sales team sell our products confidently and compliantly
• Act as a point of escalation for outside counsel and manage outside counsel relationships when matters require external expertise

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• Intellectually curious and a creative problem solver: you relish learning new products and finding creative solutions to complex and evolving legal and commercial problems
• Exceptional drafting skills, with experience in creating services terms or SaaS agreements in addition to deal negotiation drafting
• A self-starter with a bias for action: you are proactive and take ownership to move matters forward
• A clear and concise communicator (written and verbal): you can distill key risks and explain nuanced issues in plain, simple terms for commercial and technical stakeholders
• A natural collaborator: you can guide cross-functional teams toward practical, win-win outcomes
• Familiar with the legal issues and commercial risks arising in connection with hosted data and technology services
• Passionate about technology and able to understand complex business models and product use cases quickly
• A team player willing to do what it takes to contribute to collective success
• Qualified with good standing membership in at least one US state bar with a JD or foreign equivalent
• 6+ years of relevant experience in-house or in a technology practice group at a top law firm

Preferred qualifications

• Direct experience advising on, drafting service terms for, and negotiating transactions involving cryptocurrency, stablecoin, or traditional money-movement products, particularly on a global basis
• Experience in payments or fintech and familiarity with related regulatory frameworks
• Working knowledge of LLM tools and experience in improving legal processes with AI technology
• Prior in-house experience advising high-growth technology companies
• Working knowledge of data protection and privacy regimes such as CCPA, GDPR, and HIPAA

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

The Accounting Team is responsible for understanding and telling Stripe’s financial story and shaping our collective understanding of how Stripe is performing as a business. Our primary focus is maintaining a well-controlled environment that effectively supports corporate governance, financial reporting and disclosure requirements. We advise and enable Stripe to grow – supporting all products at Stripe, consulting on accounting implications and supporting teams’ ability to make informed strategic decisions. We operate in a fast-paced environment and collaborate significantly with cross-functional and international teams.

What you’ll do

Our Accounting team is seeking an innovative embedded technical resource to help us scale for the future, in a fast-paced environment that’s growing rapidly. You’ll leverage your accounting, artificial intelligence (AI), and technical expertise to build intelligent solutions that enhance Stripe’s accounting capabilities. You’ll develop AI-powered tools and models, autonomous agents, and data products that automate complex workflows and provide actionable insights within a framework of financial reporting control. Working at the intersection of artificial intelligence, accounting, and product development, you'll collaborate with engineering and finance teams to deploy cutting-edge AI applications that scale with Stripe's growth and support our mission of increasing the GDP of the internet. 

Responsibilities

• Apply your accounting and finance domain expertise to identify, explore, and prototype high-impact opportunities where AI can solve complex accounting challenges 
• Build using AI-powered tools and artificial intelligence solutions to automate accounting workflows, enhance controllership, and scale our operations
• Design and deploy autonomous AI agents using frameworks that can reason, plan, and execute complex multi-step problems and enhance decision-making processes through understanding risk and maintaining effective financial reporting controls.
• Ship and maintain interactive data products and self-service analytics tools using SQL and Python frameworks (data visualization and dashboards, low-code application building frameworks) that provide real-time insights and actionable intelligence
• Work across Accounting and partner teams to uncover efficiency opportunities, including AI use cases, document requirements, and translate complex financial workflows into well controlled technical solutions
• Partner with Accounting and SOX teams to assess and develop an effective internal controls approach to AI-based accounting solutions

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 10+ years of relevant experience, with at least 4+ years of experience in accounting related or adjacent roles (e.g. finance systems, process improvement) 
• B.A. or B.S degree in Accounting, Finance, Finance Systems or Information Systems
• Fluency in U.S. GAAP
• Advanced proficiency in SQL, including writing complex queries, using CTEs (common table expressions), window functions, and joins for data analysis and pipeline logic
• Familiarity with modern data tools (Python, Databricks, ETL/ELT processes, data pipelines) and coding with AI assistance
• Comprehensive understanding of AI fundamentals and experience with emerging AI/LLM tools, conversational interfaces, prompt engineering, or automation platforms and RPA
• Solution and results-oriented, with a focus on delivering impact in a fast-paced environment 
• Excellent communication and organizational skills, both written and verbal, with the ability to convey financial concepts to both financial and non-financial audiences
• Experience with internal controls (design, implementation and execution)

Preferred qualifications

• Familiarity with the payments industry and fintech landscape

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

AMER Demand Generation is a team of marketers and channel specialists that drives strategies to engage prospects and customers, generating demand for Stripe's prioritized solutions in the Americas. We partner closely with Global Campaigns, Partner Marketing, Product Marketing, Sales Development, and Sales to bring full-funnel campaigns to life and optimize performance and business impact.

We're seeking an experienced marketer to own the Velocity – mid-market and small businesses – segment across the US, Canada, and LATAM. This individual will design the strategy and drive strategy realization work to grow market share and drive pipeline in collaboration across the GTM organization. They will help Stripe mature its marketing approach to the Velocity audience and evolve our demand generation strategy for this high-growth segment.

What you’ll do

This business-critical role will have significant impact across Stripe's GTM organization. Stripe's Velocity segment is growing rapidly and represents a massive share of our Americas pipeline with a fundamentally unique go-to-market motion. This role will design the Velocity engine to reach the buying committee and create a consistent experience through different journeys, channels, and tactics to ensure an integrated, full-funnel experience. You'll define regional priorities, allocate budget across channels, and be the connective tissue between global campaign strategy and regional execution for this segment.

Responsibilities

• Land and tailor global campaigns to acquire and nurture Velocity prospects at scale through digital content, paid media, content syndication, digital events, targeted nurture programs, etc
• Build region-specific marketing activations with channel leads to unlock local opportunities for SMB and mid-market audiences
• Partner with regional performance media experts to acquire and re-engage AMER Velocity prospects and customers through a broad mix of paid media tactics
• Collaborate with partner marketing to build and scale the through-partner demand generation strategy for Velocity companies — a critical and growing channel for this segment
• Build a cross-GTM coalition including Global Marketing, Regional Sales, Sales Development, and Sales Operations to jointly grow the Velocity pipeline
• Own key business and revenue metrics for the Velocity segment across the sales funnel — investigating conversion, lead quality, channel mix effectiveness, and pipeline health
• Partner cross-functionally to define regional requirements as Stripe refines marketing capabilities, MarTech stack, and lead management for scaled motions
• Identify innovative new ways to reach and engage Velocity users — there is broad leeway in this role to pursue creative marketing ideas
• Be a thought leader representing the Americas as Stripe grows its Velocity go-to-market across campaigns and broader strategy

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 7+ years of experience running scaled digital demand generation programs (e.g., demand generation, growth marketing, or regional marketing) 
• Experience with GTM direct ownership of a velocity, SMB, or mid-market segment at a B2B company
• Demonstrated experience building multi-channel demand generation strategies and owning integrated digital activations across paid media, content marketing, email marketing, and events
• Demonstrated experience investigating business health and owning marketing performance metrics — able to craft actionable insights from GTM data on lead acquisition, funnel conversion, pipeline pacing, and channel effectiveness
• Strong organization and project management skills with the ability to manage multiple complex programs simultaneously
• Proven track record building and executing programs with cross-functional stakeholders including sales, sales development, partner marketing, and product marketing — expect to discuss programs where you were the directly responsible individual

Preferred qualifications

• Fluency with AI including leveraging native AI tooling and integrating LLM / agentic capabilities into everyday work
• Experience building integrated demand strategies that connect with partner marketing, through-partner channels, or ecosystem-led growth motions
• Experience marketing to SMB (sub-100 employee) and mid-market (100–1,000 employee) companies, including segmentation by industry or technical sophistication
• Experience in payments, financial technology, or infrastructure software
• Adjacent business experience (e.g., strategy consulting, sales, or sales development) that brings well-rounded GTM perspective

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

AI is moving fast and Stripe is moving fast to adopt it. But we need to make sure we do all of this safely, and for most of these tools enterprise-grade security isn't just available off the shelf. That's where the AI security team comes in - we are responsible for building and partnering to create the right security primitives to enable Stripe to move fast safely.

This is a team that will be working in the low level components of our AI stack so both infrastructure and security experience are pluses. This space is moving fast so being comfortable with ambiguity and changes in priority are a must.

This is a foundational role — you'd be the first engineer on the team.

What you’ll do

Engineers on this team will do a mixture of partnering and advising with teams building AI infrastructure and products, and building security infrastructure primitives for AI. 

One of our major focuses will be building a security tooling layer that sits in the inference path, providing detection and protection against AI specific threats like prompt injection, jailbreaks, and tool misuse.

Responsibilities

• Build security frameworks integrated with our core AI infrastructure
• Design and implement defenses against AI specific threats like prompt injection and jailbreaks
• Collaborate with other engineering teams to ensure Stripe's AI infrastructure and products are built securely
• Support other engineering teams in integrating security primitives
• Uphold our high engineering standards and improve our codebase and processes
• Design and build systems that help define the state of the art for AI security

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 5+ years of software development experience
• Experience independently designing and developing medium to large projects
• Experience working collaboratively across multiple engineering teams
• Experience writing high quality code in a major programming language
• Ability to drive clear next steps when working in an ambiguous environment
• Ability to think creatively and reason clearly in a complex problem domain

Preferred qualifications

• Experience developing, deploying, and maintaining reliable infrastructure systems
• Experience in security engineering
• Experience building AI agents or LLM-based systems

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

The Stripe Assistant team is transforming how users interact with Stripe by building an intelligent and proactive assistant that not only answers users’ queries but efficiently resolves issues and provides valuable business insights. We leverage LLMs and agentic systems to elevate the user experience across Stripe—from the dashboard to support surfaces—and we enable other teams to build and integrate their AI agents on our platform. We’re evolving from a helpful support tool to a trusted pilot that anticipates, optimizes, and executes on behalf of our users.

What you’ll do

As a Senior Machine Learning Engineer on the Stripe Assistant team, you’ll own the end-to-end ML and agent architecture that makes Stripe Assistant safe, reliable, and deeply useful. You’ll set the strategy for how the Assistant executes high-trust actions, delivers accurate analytical answers across Stripe and the broader web, orchestrates capabilities across many tools and agents, and grounds responses in authoritative Stripe and user data—so users can resolve issues quickly and confidently.

You’ll drive conversation continuity and personalization across surfaces, evolve the Assistant into a proactive partner that anticipates user needs, and deepen its presence in the dashboard to streamline critical workflows. You’ll establish rigorous evaluation and SLOs and deliver step‑change improvements in quality, latency, cost, and availability—paving the way for configurable levels of autonomy and, ultimately, a dependable operating layer over a merchant’s Stripe account.

Responsibilities

Our team operates fluidly and here are some problems you may tackle:

• Establish trustworthy, human-in-the-loop execution for high-trust “write” actions—prioritizing user control, transparency, accountability, and auditability so customers can delegate with confidence.
• Define and evolve the Assistant’s capability and governance model across hundreds of tools and agents, balancing power, permissions, and consistency at scale.
• Raise answer quality and usefulness by grounding in authoritative Stripe knowledge and live user data, building cross-surface memory and personalization, and making the Assistant proactive and present in the dashboard.
• Explore and apply optimal machine learning methods to improve Stripe Assistant’s overall performance, including but not limited to fine-tuning LLMs with RLHF, synthetic data generation, optimizing RAG pipelines via domain‑specific embedding and retriever fine‑tuning, and automatic prompt tuning, etc.
• Make quality and reliability a product: set and meet SLOs, build rigorous evaluation and benchmarking loops, and drive sustained improvements in latency, cost, and availability.
• Lead as a tech lead: mentor and grow engineers, uphold high bars for code quality, security, observability, and operational rigor, and align cross‑functionally to ship safely and fast.

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 5+ years in AI/ML and backend engineering.
• Applied LLM experience: RAG/embeddings, tool use/function calling, agentic planning/orchestration, fine-tuning, code generation, evaluations, etc.
• Proficient in Python (Ruby is a plus); strong distributed systems fundamentals.
• Experience working closely with product management, design, other engineers, and other cross-functional partners.

Preferred qualifications

• Experience operating ML systems at global scale with stringent SLOs—balancing reliability, latency, and cost—with privacy, security, and compliance by design.
• Experience building products where AI/ML is core; as well as balancing short-term product priorities with long-term AI/ML improvements.
• Track record building ML platforms, especially those that enable multiple teams to collaborate together.
• Strong technical leadership and communication: mentoring and elevating engineers, elevating AI/ML awareness and posture within organizations, setting architectural direction, and driving alignment in ambiguity.

Join us to build a trustworthy, proactive AI operating layer for every Stripe merchant—advancing safety, reliability, and insight at global scale. If you’re ready to help take Stripe Assistant from copilot to full autopilot and shape how businesses connect with Stripe, we’d love to hear from you.

Engineering at Brex

Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders.

What you’ll do

As the Engineering Manager for Cloud Infrastructure, you will lead a highly competent team of senior engineers responsible for the foundational AWS ecosystem that powers Brex. Your primary near-term mission will be driving our high-priority Business Continuity and Disaster Recovery (BCDR) initiative to completion, a company-level priority that involves multi-region failover and infrastructure-wide resilience. You will balance people leadership with deep technical involvement, earning the respect of a senior team while improving operational hygiene and cross-functional coordination across the entire engineering organization.

Where you’ll work

This role will be based in our Seattle office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week: Monday, Wednesday, and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Lead and Grow: Manage and support a senior team of 6 ICs, fostering a culture of high ownership, autonomy, and technical excellence.
• Drive BCDR Strategy: Oversee the execution of the multi-year BCDR initiative, ensuring multi-region infrastructure readiness and automated failover capabilities.
• Technical Stewardship: Maintain and scale Brex’s core cloud infrastructure, including Kubernetes (EKS), RDS/Aurora/Postgres, networking (VPC), and AWS service integrations.
• Cross-Functional Collaboration: Partner with product and engineering teams across Brex to drive adoption of new infrastructure capabilities and ensure successful migrations.
• Operational Excellence: Improve team hygiene by establishing and improving best practices for work tracking (Linear), documentation, and incident response.
• Resource Management: Effectively allocate resources to balance critical project delivery with long-term infrastructure stability.

Requirements

• Leadership Experience: 3+ years of experience directly managing software or infrastructure engineering teams.
• Technical Depth: Deep hands-on experience with cloud infrastructure foundations, specifically AWS, Kubernetes, and Postgres.
• Architectural Insight: Proven ability to design and implement complex infrastructure projects such as multi-region deployments or disaster recovery frameworks.
• Collaborative Mindset: Strong communication skills with the ability to influence technical decisions across multiple autonomous teams.
• Analytical Problem Solving: Ability to dive deep into technical issues while maintaining a high-level strategic view of organizational goals.
• Engineering Background: 5+ years of experience in software or systems engineering.

Bonus points

• Experience with Infrastructure as Code tools, specifically Terraform.
• Background in managing cloud infrastructure cost optimization programs.
• Experience with our tech stack components: Go, Kotlin, Python, or Elixir.
• Passion for leveraging AI and LLM-assisted workflows to increase engineering velocity.

Compensation

The expected salary range for this role is $240,000 - $300,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Engineering

Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders.

What you’ll do

You will lead an engineering team focused on building the systems and product experiences that power customer activation at Brex,  including onboarding, account setup, verifications, and integrations workflows that help customers realize value quickly. This role requires strategic thinking, operational excellence, technical leadership, and a deep passion for delivering frictionless, AI-enhanced customer journeys. The ideal candidate is an engineering leader with experience scaling user-facing onboarding systems, delivering high-quality product experiences, and partnering deeply across Product, Design, Operations, and GTM teams.

Where you’ll work

This role will be based in our San Francisco office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Take an active role in driving business and product strategies, championing a seamless, intuitive, and efficient onboarding experience.
• Collaborate with cross-functional partners across Product, Design, Operations, and Sales to define priorities and deliver delightful customer activation experiences.
• Leverage AI to reimagine and automate onboarding and implementation workflows, improving speed, personalization, and operational leverage.
• Drive execution of the Onboarding roadmap, ensuring timely, high-quality delivery of systems and features that help customers activate and realize value.
• Lead and manage a team of engineers, including hiring, mentoring, performance management, and establishing strong technical direction.
• Drive continuous improvement in engineering processes, technical architecture, and product quality.
• Foster a culture of innovation, collaboration, accountability, and customer obsession across the team.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 6+ years of software engineering experience with strong technical depth
• 3+ years of experience managing or leading engineers in a high-growth environment.
• Strong technical background and understanding of software development principles.
• Expertise leading full-stack engineering teams delivering end-to-end product experiences.
• Regularly works with cross-functional partners (e.g. Product, Design, Operations, Sales) and excels in driving alignment across stakeholders.
• Data-driven mindset with the ability to evaluate impact, measure funnel performance, and optimize activation metrics.
• Track record building AI-powered product experiences, including LLM-driven automation and personalization.

Bonus points

• Experience with data platforms such as Snowflake, Hex, or similar.
• Experience building systems related to onboarding, implementation, identity, workflow automation, customer lifecycle products, or other customer facing experiences.
• You have started your own technology venture or were an early technical founder/employee. We value entrepreneurial spirit & scrappiness!

Compensation

The expected salary range for this role is $240,000 - $300,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Engineering

Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders.

What you’ll do

You will lead an engineering team focused on building the systems and product experiences that power customer activation at Brex,  including onboarding, account setup, verifications, and integrations workflows that help customers realize value quickly. This role requires strategic thinking, operational excellence, technical leadership, and a deep passion for delivering frictionless, AI-enhanced customer journeys. The ideal candidate is an engineering leader with experience scaling user-facing onboarding systems, delivering high-quality product experiences, and partnering deeply across Product, Design, Operations, and GTM teams.

Where you’ll work

This role will be based in our New York office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Take an active role in driving business and product strategies, championing a seamless, intuitive, and efficient onboarding experience.
• Collaborate with cross-functional partners across Product, Design, Operations, and Sales to define priorities and deliver delightful customer activation experiences.
• Leverage AI to reimagine and automate onboarding and implementation workflows, improving speed, personalization, and operational leverage.
• Drive execution of the Onboarding roadmap, ensuring timely, high-quality delivery of systems and features that help customers activate and realize value.
• Lead and manage a team of engineers, including hiring, mentoring, performance management, and establishing strong technical direction.
• Drive continuous improvement in engineering processes, technical architecture, and product quality.
• Foster a culture of innovation, collaboration, accountability, and customer obsession across the team.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 6+ years of software engineering experience with strong technical depth
• 3+ years of experience managing or leading engineers in a high-growth environment.
• Strong technical background and understanding of software development principles.
• Expertise leading full-stack engineering teams delivering end-to-end product experiences.
• Regularly works with cross-functional partners (e.g. Product, Design, Operations, Sales) and excels in driving alignment across stakeholders.
• Data-driven mindset with the ability to evaluate impact, measure funnel performance, and optimize activation metrics.
• Track record building AI-powered product experiences, including LLM-driven automation and personalization.

Bonus points

• Experience with data platforms such as Snowflake, Hex, or similar.
• Experience building systems related to onboarding, implementation, identity, workflow automation, customer lifecycle products, or other customer facing experiences.
• You have started your own technology venture or were an early technical founder/employee. We value entrepreneurial spirit & scrappiness!

Compensation

The expected salary range for this role is $240,000 - $300,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Engineering

Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders.

What you’ll do

You will lead an engineering team focused on building the systems and product experiences that power customer activation at Brex,  including onboarding, account setup, verifications, and integrations workflows that help customers realize value quickly. This role requires strategic thinking, operational excellence, technical leadership, and a deep passion for delivering frictionless, AI-enhanced customer journeys. The ideal candidate is an engineering leader with experience scaling user-facing onboarding systems, delivering high-quality product experiences, and partnering deeply across Product, Design, Operations, and GTM teams.

Where you’ll work

This role will be based in our Seattle office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Take an active role in driving business and product strategies, championing a seamless, intuitive, and efficient onboarding experience.
• Collaborate with cross-functional partners across Product, Design, Operations, and Sales to define priorities and deliver delightful customer activation experiences.
• Leverage AI to reimagine and automate onboarding and implementation workflows, improving speed, personalization, and operational leverage.
• Drive execution of the Onboarding roadmap, ensuring timely, high-quality delivery of systems and features that help customers activate and realize value.
• Lead and manage a team of engineers, including hiring, mentoring, performance management, and establishing strong technical direction.
• Drive continuous improvement in engineering processes, technical architecture, and product quality.
• Foster a culture of innovation, collaboration, accountability, and customer obsession across the team.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 6+ years of software engineering experience with strong technical depth
• 3+ years of experience managing or leading engineers in a high-growth environment.
• Strong technical background and understanding of software development principles.
• Expertise leading full-stack engineering teams delivering end-to-end product experiences.
• Regularly works with cross-functional partners (e.g. Product, Design, Operations, Sales) and excels in driving alignment across stakeholders.
• Data-driven mindset with the ability to evaluate impact, measure funnel performance, and optimize activation metrics.
• Track record building AI-powered product experiences, including LLM-driven automation and personalization.

Bonus points

• Experience with data platforms such as Snowflake, Hex, or similar.
• Experience building systems related to onboarding, implementation, identity, workflow automation, customer lifecycle products, or other customer facing experiences.
• You have started your own technology venture or were an early technical founder/employee. We value entrepreneurial spirit & scrappiness!

Compensation

The expected salary range for this role is $240,000 - $300,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Engineering

Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders.

What you’ll do

You will lead an engineering team focused on building the systems and product experiences that power customer activation at Brex,  including onboarding, account setup, verifications, and integrations workflows that help customers realize value quickly. This role requires strategic thinking, operational excellence, technical leadership, and a deep passion for delivering frictionless, AI-enhanced customer journeys. The ideal candidate is an engineering leader with experience scaling user-facing onboarding systems, delivering high-quality product experiences, and partnering deeply across Product, Design, Operations, and GTM teams.

Where you’ll work

This role will be based in our Vancouver office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Take an active role in driving business and product strategies, championing a seamless, intuitive, and efficient onboarding experience.
• Collaborate with cross-functional partners across Product, Design, Operations, and Sales to define priorities and deliver delightful customer activation experiences.
• Leverage AI to reimagine and automate onboarding and implementation workflows, improving speed, personalization, and operational leverage.
• Drive execution of the Onboarding roadmap, ensuring timely, high-quality delivery of systems and features that help customers activate and realize value.
• Lead and manage a team of engineers, including hiring, mentoring, performance management, and establishing strong technical direction.
• Drive continuous improvement in engineering processes, technical architecture, and product quality.
• Foster a culture of innovation, collaboration, accountability, and customer obsession across the team.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 6+ years of software engineering experience with strong technical depth
• 3+ years of experience managing or leading engineers in a high-growth environment.
• Strong technical background and understanding of software development principles.
• Expertise leading full-stack engineering teams delivering end-to-end product experiences.
• Regularly works with cross-functional partners (e.g. Product, Design, Operations, Sales) and excels in driving alignment across stakeholders.
• Data-driven mindset with the ability to evaluate impact, measure funnel performance, and optimize activation metrics.
• Track record building AI-powered product experiences, including LLM-driven automation and personalization.

Bonus points

• Experience with data platforms such as Snowflake, Hex, or similar.
• Experience building systems related to onboarding, implementation, identity, workflow automation, customer lifecycle products, or other customer facing experiences.
• You have started your own technology venture or were an early technical founder/employee. We value entrepreneurial spirit & scrappiness!

Compensation

The expected salary range for this role is $240,000 CAD - $300,000 CAD. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

About the Role

The Cloud Inference team scales and optimizes Claude to serve the massive audiences of developers and enterprise companies across AWS, GCP, Azure, and future cloud service providers (CSPs). We own the end-to-end product of Claude on each cloud platform, from API integration and intelligent request routing to inference execution, capacity management, and day-to-day operations.

Within Cloud Inference, the model & inference launch team owns the validation pipeline for our inference server and load balancer on these platforms. We're responsible for every inference change — model launches, performance improvements, safeguard integrations — landing on cloud platforms with correctness, performance, and reliability intact.

This is high-leverage infrastructure work: validation has to be fast and cheap enough to run on the same accelerators that serve customers, trustworthy enough to replace manual checks, and consistent enough that a change working on Anthropic first-party means it works everywhere. This directly determines how fast frontier models and features ship to every cloud platform, and how quickly performance wins reach production — reclaiming capacity at a time when compute is our scarcest resource.

What You'll Do

• Be on the critical path for frontier model launches, bringing up inference for new model architectures and shipping them to cloud platforms in lockstep with our first-party platform
• Work with the core inference team to bring new inference features (e.g. structured sampling, prompt caching, and more) to cloud platforms, owning the platform-specific integration that gets them to production
• Identify and dive deep on the gaps that make inference behave differently across first-party and CSPs — config drift, observability, deployment patterns, hard cross-platform bugs — and fix them at the source rather than building platform-specific workarounds
• Design, build, and own the CI/CD infrastructure for the inference server and load balancer across cloud platforms, with shadow traffic, performance baselines (throughput and latency), and correctness checks that catch regressions before production
• Drive down merge-to-production cycle time by making validation faster, more parallel, and cost-effective enough to run on the same constrained accelerator pool that serves customers, without trading away reliability 
• Analyze observability data across providers to identify performance bottlenecks, cost anomalies, and regressions, and drive remediation based on real-world production workloads

You May Be a Good Fit If You:

• Have a strong interest in LLM serving; prior inference or ML experience is not required 
• Have significant software engineering experience, with a strong background in high-performance, large-scale distributed systems serving millions of users
• Have a track record of building automation or test infrastructure that measurably improved release velocity or reliability
• Have experience building or operating services on at least one major cloud platform (AWS, GCP, or Azure), with exposure to Kubernetes, Infrastructure as Code, or container orchestration
• Thrive in cross-functional collaboration with both internal teams and external partners
• Are a fast learner who can quickly ramp up on new technologies, hardware platforms, and provider ecosystems
• Are highly autonomous and take ownership of problems end-to-end, including work that falls outside your job description

Strong Candidates May Also Have Experience With:

• LLM inference optimization, batching, and caching strategies
• Capacity-constrained scheduling or shared-resource test infrastructure
• Solid understanding of multi-region deployments, request routing, load balancing, global traffic management
• Working with CSP partner teams to scale infrastructure across multiple platforms, navigating differences in networking, security, privacy, and managed service
• Proficiency in Python or Rust

Join Airtable as a Product Security Engineer and play a pivotal role in shaping the security of our rapidly evolving platform as we expand our AI and LLM-powered offerings. You will join the team responsible for safeguarding the application layer of Airtable’s platform.

You will partner closely with product engineering teams to build paved roads, frameworks, and automated controls that make the secure path the easy path for our engineering teams. You will help influence application security at scale, ensuring our products are secure by design.

What you'll do

• Develop self-service security frameworks and "paved roads" that allow engineering teams to ship secure code by default.
• Focus on automated guardrails for common vulnerabilities, while prioritizing deep-dive design reviews into complex business logic and data isolation issues (for example, multi-tenant isolation and authorization/permission bypasses) that automated tools cannot catch.
• Partner with product and engineering teams to review designs early, contribute to threat modeling for new features and complex initiatives, and provide clear, actionable security guidance.
• Research emerging threats and evolving best practices, specifically regarding AI and LLM safety, and implement controls to secure these workflows.
• Manage and evolve our approach to external penetration testing and bug bounties, driving remediation for findings and treating vulnerability management as an engineering problem.
• Contribute to the long-term roadmaps, metrics, and strategic planning for the security team.
• (Senior/Staff L5+) Lead complex threat modeling sessions for major product launches and define secure coding standards, and actively mentor other engineers to raise the technical security bar across the organization.

Who you are

• 4+ years of experience in product security or application security, with experience shipping production code. Please note this is not an early career position.
• You have a strong background in computer science or a related field, with proficiency in writing clean, maintainable code.
• You have deep familiarity with JavaScript or TypeScript, Node.js, and modern web application frameworks, and can reason about the security implications of systems built on them.
• You have hands-on experience securing LLM integrations and identifying prompt injection or data leakage risks.
• You are proficient in writing and reviewing code and treat security as an engineering problem to be solved with software, not just policies.
• You excel at communicating complex security risks to non-security stakeholders and enjoy collaborating cross-functionally to find solutions that balance security with engineering velocity.
• You are comfortable working in a fast-paced environment, navigating ambiguity, continuously learning about emerging threats and technologies, and contributing to long-term security strategy.

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

VEVRAA-Federal Contractor

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

#LI-remote

About the Role

We are seeking a GRC Automation Lead to join our GRC organization and build the technical foundation for how we scale our risk and compliance programs. In this role, you will lead the team that designs and implements automated workflows, data pipelines, and integrations that transform manual compliance processes into scalable engineering systems. 

This is a greenfield opportunity to establish the team, architecture, and integrations that will define how we approach governance, risk, and compliance at Anthropic. The core challenge is a data problem: compliance information lives across dozens of systems—cloud infrastructure, identity providers, HR platforms, ticketing tools, code repositories—and your job is to design systems that bring it together, normalize it, and make it actionable. Success in this role comes from understanding how systems connect and how data flows between them, not from writing code yourself.

At Anthropic, you'll also have a unique advantage: the ability to design AI-powered workflows where Claude acts as an extension of your team, handling tasks that would traditionally require additional headcount or manual effort. You'll need ingenuity to identify where agentic AI can accelerate evidence collection, interpret unstructured data, triage compliance gaps, and augment human judgment in risk assessments. Working closely with Security, IT, and Engineering teams, you'll translate compliance and regulatory requirements into solutions that support audit programs including SOC 2, ISO, HIPAA, and FedRAMP, building systems that combine traditional automation with AI capabilities to achieve scale that wouldn't otherwise be possible.

Responsibilities: 

• Lead the team that establishes foundational GRC processes and architecture. Design and build automated workflows for risk management and compliance, creating scalable systems that enable continuous monitoring as Anthropic grows.
• Build data pipelines that aggregate risk, control, and asset information from across our technology stack. This means solving hard data integration problems: mapping disparate schemas, handling inconsistent data quality, and creating unified views of compliance posture through dashboards and reporting tools.
• Inform GRC platform strategy and implementation: in partnership with other programs, evaluate, select, and deploy tooling that meets our compliance requirements.
• Translate written policies and compliance requirements into policy-as-code—working with Engineering and Security teams to express requirements as enforceable rules, automated checks, and continuous validation rather than static documents.
• Establish feedback loops between policy and implementation: surface where technical controls diverge from written requirements, identify where policies need to evolve based on infrastructure realities, and ensure that compliance requirements are expressed in terms engineers can act on.
• Design and deploy agentic AI workflows that extend team capacity, using Claude to serve as a virtual GRC analyst to automate evidence analysis, monitor control effectiveness, draft audit responses, interpret policy documents, and handle other tasks that require reasoning over unstructured information.
• Design and maintain integrations connecting GRC tooling with cloud infrastructure, identity management systems, HRIS platforms, ticketing systems, version control, and CI/CD pipelines—working with engineers to implement integrations that enable automated evidence collection and continuous compliance validation.
• Build and lead an AI-forward GRC engineering function as we scale: hiring team members, establishing practices, and defining the technical roadmap for governance and compliance automation at Anthropic.

You may be a good fit if you:

• Have 12+ years of total experience and 3-4+ years of experience managing technical individual contributors or systems-focused teams, with a proven track record of building or scaling small teams (2-5 people) in security, compliance, automation, or operations functions.
• Are a systems thinker first. You understand how complex environments work: how data flows between systems, where integration points exist, what breaks when systems don't talk to each other. Your strength is designing the right architecture and environment for security monitoring, not necessarily implementing it yourself.
• Have 5+ years of experience designing automated workflows, data pipelines, or system integrations, whether through traditional development, low-code platforms, GRC tools, or process automation. We care about your ability to solve integration problems more than your programming language proficiency.
• Have a relentless focus on data integration: you understand how to pull data from multiple sources, normalize it, join it meaningfully, and surface insights. You're comfortable reasoning about messy, inconsistent data and designing systems that handle edge cases gracefully.
• Understand APIs and integration patterns: REST APIs, webhooks, authentication flows, polling vs. push architectures, and can evaluate systems based on how well they expose data and support automation.
• Can work independently with minimal guidance, taking ownership of complex problems from design through implementation while managing ambiguity inherent in early-stage programs.
• Have strong analytical and problem-solving skills with attention to detail necessary for compliance work, balanced with pragmatism about risk-based prioritization in fast-paced environments.

Strong candidates may have:

• Experience designing or implementing AI-powered automation, agentic workflows, or LLM-based tooling in operational contexts.
• Experience with GRC platforms such as ServiceNow GRC, Vanta, Drata, OneTrust, RSA Archer, or similar tools including configuration, customization, and integration capabilities
• Familiarity with scripting languages (Python or similar) for automation tasks, API interactions, and data transformation.
• Prior experience in high-growth startup environments demonstrating ability to build scalable processes and adapt quickly to changing requirements and priorities
• Familiarity with Infrastructure as Code tools (Terraform, CloudFormation, Ansible) and DevSecOps practices including CI/CD pipeline integration and policy-as-code implementations.
• Familiarity with cloud platforms (AWS, GCP, Azure) and an understanding of how compliance-relevant data can be extracted from their APIs and logging systems.

Deadline to apply: None, applications will be received on a rolling basis.

ABOUT US

At RADAR, we're transforming the way the world thinks about physical retail. RADAR has raised over $104M from top investors, retailers, and strategics and works with some of the world's retail brands including American Eagle and Gap. We’re building the future of in-store experience where every product and every person can be precisely located in real time.

Our platform combines RFID and AI to unlock hyper-accurate product visibility and automation at scale. From real-time inventory tracking to seamless checkout experiences, our technology empowers some of the world’s largest retailers to streamline operations, reduce loss, and elevate both employee and customer experiences.

We’re a fast-growing, mission-driven startup where bold ideas, collaboration, and impact are at the core of everything we do. Join us as we reshape the physical world with digital precision, starting with retail and expanding far beyond!

OUR VALUES

Mission-Driven: We're transforming retail with cutting-edge technology and building something that truly matters.

Collaborative Team: We thrive on curiosity, shared goals, and solving complex problems together.

High Impact: You’ll make meaningful contributions from day one and help shape the future of our product and company.

Clear Communication: We value honesty, humility, and respectful dialogue—everyone’s voice matters.

Balanced Lives: We work hard, but not at the expense of well-being. We respect time, boundaries, and life outside of work.

Diverse Perspectives: We believe better ideas come from diverse backgrounds, experiences, and viewpoints.

Empathy-Driven Design: We build with deep respect for our end users, listening closely to their feedback and needs.

ABOUT THE JOB

As a Software Engineering Manager, you will be a player-coach leading a high-caliber engineering team building advanced platforms. Depending on your area of ownership, you may lead one or more teams across domains including Control Plane (edge/cloud compute), Dev/Sec Ops, Data Platform & Governance, High Scale Event Processing (hundreds of billions of events per day), Mobile Platforms, SRE & Operations, or Radar Platform (our core web/cloud customer experience). You will be technically hands-on in delivery while setting strategic direction, growing engineers, and collaborating cross-functionally with stakeholders and partner teams.

The best engineering managers here are strong engineers first. You'll be expected to contribute meaningfully to design, review code, and engage deeply with technical problems, not just manage the process around them. We move fast, and you've done it before. You know how to maintain a high quality bar without sacrificing velocity, and you bring the judgment to know when to push and when to slow down just enough to get it right.

Responsibilities:

• Lead, mentor, and grow a team of talented engineers; own performance management, career development, and a strong team culture.
• Set technical direction, support architecture decisions, and champion engineering best practices across your team and peers.
• Contribute directly to solution design and technical reviews; maintain a strong, credible technical presence.
• Manage agile processes, execution priorities, and on-time delivery of high-quality solutions.
• Collaborate with Engineering, Product, and UX stakeholders to define project plans and ensure requirements are understood, met, and well-documented.
• Identify, communicate, and drive resolution for technical and organizational risks.
• Foster a culture of security, quality, operational accountability, and continuous improvement.
• Support hiring and help grow the broader engineering organization.

ABOUT YOU

Required:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 7+ years of software engineering experience, including at least 2 years managing engineering teams of 5 or more direct reports.
• Proven ability to remain technically hands-on: contributing to design, architecture, and code review as a practicing engineer, not just an overseer.
• Demonstrated experience building, deploying, and operating complex distributed systems.
• Proficiency in at least one core language: Java, Python, C++, or Go.
• Solid foundation in systems or cloud architecture, DevOps/SecOps practices, automation, and CI/CD pipelines.
• Excellent communication, organizational, and people leadership skills.
• Commitment to engineering best practices: code quality, testing, and operational stability.
• Demonstrated ability to move fast and deliver in a startup or high-growth environment without compromising quality.

Preferred:

• Prior experience leading teams in one or more domains: Control Plane, Dev/Sec Ops, Data Platform, High Scale Event Processing, Mobile Platforms, SRE, or Radar Platform.
• Experience guiding teams through growth, change, and cross-functional collaboration.
• Familiarity with cloud platforms (AWS, GCP, Azure), container orchestration, or real-time data processing.
• Passion for mentoring, technical empowerment, and building inclusive engineering culture.

WHAT YOU'LL DO

In your first 30 days, you will:

• Meet every direct report 1:1 and begin building trust and rapport.
• Shadow team rituals: standups, planning, retros, design reviews.
• Map the systems your team owns: architecture, dependencies, operational health.
• Meet key cross-functional partners: product, design, peer engineering teams.
• Identify any immediate fires or risks that need attention before deeper learning is complete.

In your first 60 days, you will:

• Establish a consistent 1:1 cadence and begin individual development conversations.
• Actively participate in design and architecture discussions; contribute to code and technical reviews.
• Clarify team goals, priorities, and near-term delivery commitments.
• Identify process or quality gaps and begin forming a point of view on how to address them.
• Deliver or unblock at least one meaningful piece of work alongside your team.

In your first 90 days, you will:

• Present an initial team roadmap or priority framework to your manager and stakeholders.
• Have a clear development plan in place for each direct report.
• Be actively driving execution: unblocking the team, removing friction, and holding a high bar.
• Own at least one cross-functional initiative or decision end-to-end.
• Have a concrete plan to improve one dimension of team health: quality, velocity, culture, or process.

At RADAR, your base pay is one part of your total compensation package. The expected base salary range for this position is $200,000 - $250,000. Individual pay is determined by work location and additional factors,  including job-related skills, experience and relevant education or training.You will also be eligible to receive other benefits including: equity, comprehensive medical and dental coverage, life and disability benefits, 401k plan,  flexible time off, and paid parental leave. The pay range listed for this position is a good faith and reasonable estimate of the range of possible base compensation at the time of posting. 

Research has shown that women & underrepresented minorities are more likely to read lists of requirements and consider themselves unqualified if they don't meet every single one. This list represents what we're ideally looking for, but everyone has unique strengths & weaknesses, and we hire for strength & potential, not lack of weakness.

Use of artificial intelligence or a LLM such as ChatGPT during the interview process will be grounds for rejection of your application process.

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

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

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

What You’ll do:

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

Key Metrics

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

What You’ll Add to DigitalOcean:

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

Preferred

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

Compensation Range: 

• $195,000 - $239,000

*This is a hybrid role

JR: 2026-7748

#LI-Hybrid

About Scale

At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, fueling the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re amplifying access to high-quality data to drive progress toward Artificial General Intelligence (AGI). Building on our history of model evaluation with enterprise and government customers, we are expanding our capabilities to set new standards for both public and private evaluations.

About This Role

This role operates at the forefront of AI research and real-world implementation, with a strong focus on reasoning within large language models (LLMs). The ideal candidate will study the data types critical for advancing LLM-based agents, including browser and software engineering (SWE) agents. You will play a key role in shaping Scale’s data strategy by identifying the most effective data sources and methodologies for improving LLM reasoning. Success in this role requires a deep understanding of LLMs, planning algorithms, and novel approaches to agentic reasoning, as well as creativity in tackling challenges related to data generation, model interaction, and evaluation. You will contribute to impactful research on language model reasoning, collaborate with external researchers, and work closely with engineering teams to bring state-of-the-art advancements into scalable, real-world solutions.

Ideally, you’d have:

• Practical experience working with LLMs, with proficiency in frameworks like PyTorch, JAX, or TensorFlow. You should also be skilled at rapidly interpreting research literature and turning new ideas into working prototypes.

• A track record of published research in top ML and NLP venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, CoLLM, etc.).

• At least three years of experience solving complex ML challenges, either in a research setting or product development, particularly in areas related to LLM capabilities and reasoning.

• Strong written and verbal communication skills, along with the ability to work effectively across teams.

Nice to have:

• Hands-on experience fine-tuning open-source LLMs or leading bespoke LLM fine-tuning projects using PyTorch/JAX.

• Research and practical experience in building applications and evaluations related to LLM-based agents, including tool-use, text-to-SQL, browser agents, coding agents, and GUI agents.

• Experience with agent frameworks such as OpenHands, Swarm, LangGraph, or similar.

• Familiarity with advanced agentic reasoning techniques such as STaR and PLANSEARCH.

• Proficiency in cloud-based ML development, with experience in AWS or GCP environments.

Our research interviews are designed to assess candidates' ability to prototype and debug ML models, their depth of understanding in research concepts, and their alignment with our organizational culture. We do not conduct LeetCode-style problem-solving assessments.

As the leading data and evaluation partner for frontier AI companies, Scale is dedicated to advancing the evaluation and benchmarking of large language models (LLMs). We are building industry-leading LLM evals, setting new standards for model performance assessment. Our mission is to develop rigorous, scalable, and fair evaluation methodologies to drive the next generation of AI capabilities.

Our Research teams work with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. As a Staff Machine Learning Research Scientist on the LLM Evals team, you will lead the development of novel evaluation methodologies, metrics, and benchmarks to measure the capabilities and limitations of frontier LLMs. You will help define what "good" looks like in generative AI, driving research that informs both our internal roadmap and the broader research community. This role is critical for designing and executing a roadmap that defines best practices in data driven AI development and will accelerate the next generation of generative AI models in partnership with top foundational model labs.

You will:

• Drive research on the effectiveness and limitations of existing LLM evaluation techniques.
• Design and develop novel evaluation benchmarks for large language models, covering areas such as instruction following, factuality, robustness, and fairness. 
• Communicate, collaborate, and build relationships with clients and peer teams to facilitate cross-functional projects.
• Collaborate with internal teams and external partners to refine metrics and create standardized evaluation protocols.
• Implement scalable and reproducible evaluation pipelines using modern ML frameworks.
• Publish research findings in top-tier AI conferences and contribute to open-source benchmarking initiatives.
• Mentor and guide research scientists and engineers, providing technical leadership across cross-functional projects.
• Stay deeply engaged with the ML research community, tracking emerging work and contributing to the advancement of LLM evaluation science.
• Thrive in a high-energy, fast-paced startup environment and are ready to dedicate the time and effort needed to drive impactful results.

Ideally you'd have:

• 5+ years of hands-on experience in large language model, NLP, and Transformer modeling, in the setting of both research and engineering development
• Experience and track of recording in landing major research impacts in a fast-paced environment
• Experience tech leading a team of research scientists and research engineers
• Excellent written and verbal communication skills
• Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals
• Previous experience in a customer facing role.

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities.

About the General Agents Team

The General Agents team, part of Scale’s Enterprise organization, builds robust general agents for customer use cases and applications. The team sits at the intersection of frontier agent development and real-world deployment, translating state-of-the-art reasoning and agentic capabilities into reliable, production-grade systems that drive real economic value. Our agents are scalable systems built around recurring enterprise problem domains, with a strong emphasis on generalization, extensibility, and deployment across many customers.

About the Role

As a Senior/Staff Machine Learning Engineer (MLE) on the General Agents team, you’ll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems. You will work across the full agent lifecycle—from model and system design to evaluation, deployment, and iteration—bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments.

You will:

• Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases.
• Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints.
• Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings.
• Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs.
• Productionize frontier agent techniques (e.g., planning, multi-step reasoning and tool-use, multi-agent patterns) into maintainable, observable systems.
• Own deployment, monitoring, and iteration of agent systems, including failure analysis and continuous improvement based on real-world usage.
• Contribute to technical direction and architectural decisions for general agent development best practices and methods, with increasing scope and leadership at the Staff level.

Ideally you’d have:

• 5+ years of experience building and deploying machine learning or AI systems for real-world, production use cases.
• Strong engineering fundamentals, supported by a Bachelor’s and/or Master’s degree in Computer Science, Machine Learning, AI, or equivalent practical experience.
• Deep understanding of modern LLMs, prompt-, context-, and system-level optimization, and agentic system design.
• Proven proficiency in Python, including writing production-quality, testable, and maintainable code.
• Experience building systems that integrate models with external tools, APIs, databases, and services.
• Ability to operate in ambiguous problem spaces, balancing research-driven approaches with pragmatic product constraints.
• Strong communication skills and comfort working in customer-facing or cross-functional environments.

Nice-to-haves:

• Hands-on experience building AI agents using modern generative AI stacks (OpenAI APIs, commercial or open-source LLMs).
• Experience with agent frameworks, orchestration layers, or workflow systems (e.g., tool calling, planners, multi-agent setups).
• Familiarity with evaluation, monitoring, and observability for LLM-powered systems in production.
• Experience deploying ML systems in cloud environments and operating them at scale.
• Experience fine-tuning or adapting foundation models using methods like supervised fine-tuning (SFT), reinforcement learning with verifiable rewards (RLVR), and low-rank adaptation (LoRA) to improve agent performance on domain-specific tasks.
• Interest in shaping the future of general-purpose enterprise agents and their real-world impact.

About Scale

At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations.

About the ACE team 

The Agent Capabilities & Environments (ACE) team, part of Scale’s Research organization, brings together customer-facing Researchers and Applied AI Engineers. Our core mission includes research on agent environments and RL reward signals, benchmarking autonomous agent performance across real-world scenarios and environments, creating robust data programs to improve Large Language Models (LLMs) agentic capabilities and building foundational tools and frameworks for evaluating models as agents. ACE focuses on autonomous agents that dynamically interact with diverse external environments, including code repositories, GUI interfaces, browsers, and more. 

About This Role

This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation. This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluation. You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate these advancements into real-world, scalable solutions.

Ideally you’d have: 

• Practical experience working with LLMs, with proficiency in frameworks like Pytorch, Jax, or Tensorflow. You should also be adept at interpreting research literature and quickly turning new ideas into prototypes.
• A track record of published research in top ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, COLM, etc.)
• At least three years of experience addressing sophisticated ML problems, either in a research setting or product development.
• Strong written and verbal communication skills and the ability to operate cross-functionally. 

Nice to have:

• Hands-on experience with open source LLM fine-tuning or involvement in bespoke LLM fine-tuning projects using Pytorch/Jax. 
• Hands-on experience and publications in building applications and evaluations related to AI agents such as tool-use, text2SQL, browser agents, coding agents and GUI agents.
• Hands-on experience with agent frameworks such as OpenHands, Swarm, LangGraph, etc.
• Familiarity with agentic reasoning methods such as STaR and PLANSEARCH 
• Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.

Our research interviews are crafted to assess candidates' skills in practical ML prototyping and debugging, their grasp of research concepts, and their alignment with our organizational culture. We will not ask any LeetCode-style questions.

As the leading data and evaluation partner for frontier AI companies, Scale is dedicated to advancing the evaluation and benchmarking of large language models (LLMs). We are building industry-leading LLM evals, setting new standards for model performance assessment. Our mission is to develop rigorous, scalable, and fair evaluation methodologies to drive the next generation of AI capabilities.

Our Research teams work with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. As the Tech Lead Manager of the LLM Evals Research team, you will lead a talented team of research scientists and research engineers focused on developing and implementing novel evaluation methodologies, metrics, and benchmarks to assess the capabilities and limitations of our cutting-edge LLMs. This role is critical for designing and executing a roadmap that defines best practices in data driven AI development and will accelerate the next generation of generative AI models in partnership with top foundational model labs. 

You will:

• Lead a team of highly effective research scientists and research engineers on LLM evals.
• Conduct research on the effectiveness and limitations of existing LLM evaluation techniques.
• Design and develop novel evaluation benchmarks for large language models, covering areas such as instruction following, factuality, robustness, and fairness. 
• Communicate, collaborate, and build relationships with clients and peer teams to facilitate cross-functional projects.
• Collaborate with internal teams and external partners to refine metrics and create standardized evaluation protocols.
• Implement scalable and reproducible evaluation pipelines using modern ML frameworks.
• Publish research findings in top-tier AI conferences and contribute to open-source benchmarking initiatives.
• Remain up-to-date on ongoing research in the team, help work through technical challenges, and be involved in design decisions
• Remain deeply involved in the research community, both understanding trends, and setting them
• Thrive in a high-energy, fast-paced startup environment and are ready to dedicate the time and effort needed to drive impactful results.

Ideally you'd have:

• 5+ years of hands-on experience in large language model, NLP, and Transformer modeling, in the setting of both research and engineering development
• Experience and track of recording in landing major research impacts in a fast-paced environment
• Experience supporting and leading a team of research scientists and research engineers
• Excellent written and verbal communication skills
• Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals
• Previous experience in a customer facing role.

Scale’s ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform has been powering MLEs, researchers, data scientists and operators for fast and automatic training and evaluation of LLM's, as well as evaluation of data quality.

Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely across Scale’s ML teams and researchers to build the foundation platform that supports all our ML research and development. You will be building and optimizing the platform to enable our next generation of LLM training, inference and data curation.

If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you!

You will:

• Build, profile and optimize our training and inference framework
• Collaborate with ML teams to accelerate their research and development and enable them to develop the next generation of models and data curation
• Research and integrate state-of-the-art technologies to optimize our ML system

Ideally you’d have:

• Strong excitement about system optimization
• Experience with multi-node LLM training and inference
• Experience with developing large-scale distributed ML systems
• Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. 
• Strong written and verbal communication skills and the ability to operate in a cross functional team environment

Nice to haves:

• Demonstrated expertise in post-training methods &/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc.

Scale works with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling). This role will focus on optimizing data curation and eval to enhance LLM capabilities in both text and multimodal modalities.

In this role, you will develop novel methods to improve the alignment and generalization of large-scale generative models. You will collaborate with researchers and engineers to define best practices in data-driven AI development. You will also partner with top foundation model labs to provide both technical and strategic input on the development of the next generation of generative AI models.

You will:

• Research and develop novel post-training techniques, including SFT, RLHF, and reward modeling, to enhance LLM core capabilities in both text and multimodal modalities.
• Design and experiment new approaches to preference optimization.
• Analyze model behavior, identify weaknesses, and propose solutions for bias mitigation and model robustness.
• Publish research findings in top-tier AI conferences.

Ideally you’d have:

• Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field.
• Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning.
• Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning.
• Excellent written and verbal communication skills

• Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals
• Previous experience in a customer facing role.

Voyager is an innovative defense, national security and space technology company committed to advancing and delivering transformative, mission-critical solutions. We tackle the most complex challenges to unlock new frontiers for human progress, fortify national security, and protect critical assets to lead in the race for technological and operational superiority from ground to space. 

Forge the Future: Join Voyager Technologies 

The future belongs to those who build it. At Voyager Technologies, we’re building technologies that protect lives, expand frontiers and prepare us for what’s next. And we’re doing that with people who are wired to solve, build, adapt and lead. These roles are not for the faint of heart.  

You’ll help lay the foundation for humanity's future. Join a culture where innovation thrives, curiosity is rewarded, and impact is real. We’re a company of doers, thinkers and builders, united by purpose and grounded in reality. 

If you want to put your skills to work where the stakes are real and the mission is bigger than any one person, forge the future with Voyager. 

____________________________________________________________________________________ 

Job Summary: 

We are seeking a Principal Technical Director, AI-Enabled Spectrum Dominance to serve as the senior technical leader for our advanced RF systems, software, algorithms, and agentic AI portfolio as applied to space-based and terrestrial electromagnetic warfare and sensing. In this pivotal role, you will drive the technical vision for the future of spectrum dominance while simultaneously leading the application of Voyager’s Agentic Computational Engineering (ACE) platform to RF hardware systems and digital signal processing (DSP) development.

This role uniquely combines deep RF domain expertise with leadership over AI-driven hardware design and simulation workflows. You will oversee how agentic AI systems are deployed to compress RF hardware development cycles—from antenna design and transceiver architecture to DSP algorithm development and system-level integration—accelerating the path from concept to deployable, mission-critical capability for the warfighter.

The right person has deep familiarity with hardware, software, and algorithms across a variety of RF functions, including communications, electronic warfare (EW), radar, and sensing, with particular emphasis on space-based active and passive RF systems. You must be as comfortable defining and executing complex research and development programs as you are productizing outcomes into monetizable commercial motions. You must also have the vision and technical fluency to direct how multi-agent AI platforms transform traditional RF engineering workflows.

You will be joining the Advanced Technology Development team, a specialized unit within our Strategic Growth and Technology Organization. This team is responsible for defining and developing Voyager’s future technologies, with a relentless focus on high-impact, high-ROI technology and product R&D. You will work at the intersection of Voyager’s Spectrum Dominance portfolio and the Agentic Computational Engineering (ACE) team—the group building Voyager’s Generative Engine, the AI-native platform that compresses complex hardware development cycles from years to days.

You will be joining the Advanced Technology Development team, a specialized unit within our Strategic Growth and Technology Organization. This team is responsible for defining and developing Voyager's future technologies, with a relentless focus on high-impact, high-ROI technology and product research and development. Our technology portfolio spans the totality of Voyager's capabilities and beyond—we are tasked with creating both leap-ahead capabilities in existing technology areas and strategically moving into and developing foundational technology in new, uncharted areas.

Responsibilities:  

• Technical Leadership & Vision

  • Define and drive the technical roadmap for Voyager’s Spectrum Dominance portfolio, serving as the ultimate technical authority for RF, EW, radar, and sensing programs—with specific emphasis on space-based active and passive RF systems.
  • Set the strategic direction for applying Agentic Computational Engineering to RF hardware design, DSP algorithm development, and end-to-end RF system integration.
  • Own the vision for how AI agents are used across the RF hardware design lifecycle, from generative antenna and front-end design through automated DSP algorithm synthesis and simulation-in-the-loop optimization.

  Agentic Computational Engineering for RF & DSP

  • Lead and oversee the deployment of Voyager’s ACE platform (the Generative Engine) for RF-specific applications, ensuring AI agents can autonomously design, simulate, evaluate, and optimize RF hardware and DSP subsystems.
  • Direct the development of domain-specific AI agents for RF engineering workflows—including agents for electromagnetic simulation, transceiver architecture exploration, waveform design, interference analysis, and signal chain optimization.
  • Partner with the ACE platform team to define requirements for agent orchestration, physics simulation integration (EM solvers, thermal analysis, signal integrity), and design-for-manufacturing constraints specific to space-qualified RF hardware.
  • Establish automated simulation loops between RF/DSP design agents and high-fidelity physics solvers, including meshing, solving, and post-processing for antenna patterns, RCS analysis, link budgets, and spectral performance.
  • Drive adoption of AI-first workflows across the RF engineering organization, championing use of LLM-based tools and agents to accelerate documentation, design review, test planning, and compliance verification.

  R&D Execution

  • Lead the execution of complex, high-stakes research and development programs for next-generation space-based and terrestrial RF systems, ensuring technical risks are managed and innovative solutions are delivered on schedule.
  • Oversee the design, analysis, and testing of advanced RF systems including satellite communications payloads, space-based SIGINT/ELINT collectors, synthetic aperture radar (SAR), and passive RF sensing architectures.

  End-to-End System Architecture

  • Architect complete RF systems bridging DSP algorithms, software-defined radio (SDR) hardware, FPGA/SoC platforms, and high-level mission software, ensuring seamless integration across the entire signal chain for both space and ground segments.
  • Define system architectures for space-based RF payloads that account for the unique constraints of the orbital environment: radiation tolerance, thermal management, power budgets, size/weight limitations, and long-duration mission reliability.

  Productization & Commercialization

  • Bridge the “valley of death” by guiding technologies from TRL 3–6 research efforts into robust, productized solutions ready for manufacturing and deployment. Work closely with product and business teams to define commercialization strategies.
  • Leverage agentic AI capabilities to accelerate productization timelines, using the Generative Engine to rapidly iterate on design variants and manufacturing-ready configurations.

  Team Building & Mentorship

  • Build and inspire a world-class engineering team spanning RF hardware, DSP, and AI-enabled design disciplines. Mentor senior engineers and researchers, fostering a culture of technical rigor, creativity, and rapid iteration.
  • Grow and lead a multidisciplinary team that includes RF engineers, DSP developers, and AI/ML engineers working collaboratively on agentic RF design capabilities.

  Cross-Functional Collaboration

  • Partner with business development and capture teams to shape new opportunities, providing technical grounding to win major government contracts.
  • Collaborate with the ACE platform team, propulsion, electronics, and manufacturing domain teams to ensure RF-specific agentic capabilities integrate seamlessly with Voyager’s broader Generative Engine ecosystem.

Required Qualifications:  

• Bachelor’s degree in Electrical Engineering, Physics, Mathematics, or a related field.
• Must be eligible to obtain and maintain a US Government clearance (requires US citizenship).
• Space-Based RF Systems Expertise: Demonstrated background in the design, development, and deployment of space-based active RF systems (such as satellite communications transponders, SAR payloads, space-based radar, or active phased arrays for orbital platforms) and/or passive RF systems (such as space-based SIGINT/ELINT collectors, radiometers, or passive sensing payloads). Must have direct experience with the unique constraints of the space environment, including radiation hardening, thermal management, power budgeting, and long-duration reliability.
• Deep RF & Systems Expertise: Proven background in designing and developing complete end-to-end RF systems (both RF front-ends and digital subsystems). Deep understanding of the physics of the spectrum and the hardware required to dominate it across communications, EW, radar, and sensing domains.
• SDR Proficiency: Extensive experience designing and developing complex software-defined radio (SDR) systems, including familiarity with modern transceiver architectures and FPGA/SoC platforms.
• Algorithm Development: Strong track record in designing and developing complex digital signal processing (DSP) and RF Machine Learning (RFML) algorithms. Understands how to apply modern compute—including AI/ML techniques—to solve traditional RF problems.
• R&D Leadership: Demonstrated experience leading multi-disciplinary engineering teams (Hardware, Software, RF, FPGA, AI/ML) through the full lifecycle of advanced R&D programs, from white paper to prototype to deployment.
• Domain Expertise: Demonstrated background fielding capability in one or more of the relevant spectrum dominance domains: SIGINT, EW, or Radar, with preference for space-based applications.
• Programmatic Execution: Familiarity with the unique challenges of government R&D contracting, including experience delivering against technical milestones for customers like DARPA, ONR, AFRL, NRO, or the Space Force.
• Proposal Development: Proven proposal development experience, including contributing to technical volumes and cost estimations for complex government solicitations.

Preferred Qualifications:  

• Master’s or PhD in Electrical Engineering, Physics, Mathematics, or a related field.
• Active U.S. Top Secret / SCI Security Clearance.
• Direct experience with space-based RF payload programs (design, integration, test, and on-orbit operations) for DoD or Intelligence Community customers.
• Experience with or strong interest in AI-driven engineering workflows, including agentic AI systems, LLM-based design tools, automated simulation frameworks, or generative design platforms.
• Familiarity with agent orchestration frameworks (e.g., LangGraph, AutoGen, or custom agent runtimes) and an understanding of how multi-agent systems can be applied to hardware design problems.
• Experience with electromagnetic simulation tools (HFSS, CST, FEKO, or equivalent) and a vision for how AI agents can automate and accelerate simulation-driven RF design.
• Experience productizing advanced R&D into monetizable commercial motions, demonstrating a track record of turning science projects into shipping products.
• Demonstrated history of leading winning proposals for space-based RF programs.
• Background in orbit-specific RF considerations: Doppler compensation, atmospheric propagation effects, space-to-ground link budgets, anti-jam architectures, and low-probability-of-intercept (LPI) waveforms.
• Willingness to travel up to 25% to customer sites, test ranges, and Voyager locations.

Please click “Apply” to submit your application. 

Voyager offers a comprehensive, total compensation package, which includes competitive salary, a discretionary annual bonus plan, paid time off (PTO), a comprehensive health benefit package, retirement savings, wellness program, and various other benefits. When you join our team, you’re not just an employee; you become part of a dynamic community dedicated to innovation and excellence.

Voyager is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.  

Minority/Female/Disabled/Veteran 

The statements contained in this job description are intended to describe the general content and requirements for performance of this job. It is not intended to be an exhaustive list of all job duties, responsibilities, and requirements. This job description is not an employment agreement or contract. Management has the exclusive right to alter the scope of work within the framework of this job description at any time without prior notice. 

Voyager is an innovative space, defense, and national security technology company committed to advancing and delivering transformative, mission-critical solutions. We tackle the most complex challenges to unlock new frontiers for human progress, fortify national security, and protect critical assets to lead in the race for technological and operational superiority from ground to space. 

Forge the Future: Join Voyager Technologies 

The future belongs to those who build it. At Voyager Technologies, we’re building technologies that protect lives, expand frontiers and prepare us for what’s next. And we’re doing that with people who are wired to solve, build, adapt and lead. These roles are not for the faint of heart.  

You’ll help lay the foundation for humanity's future. Join a culture where innovation thrives, curiosity is rewarded, and impact is real. We’re a company of doers, thinkers and builders, united by purpose and grounded in reality. 

If you want to put your skills to work where the stakes are real and the mission is bigger than any one person, forge the future with Voyager. 

We are seeking a Principal Electrical Engineer to lead PCB design within the Agentic Computational Engineering (ACE) platform team and to encode the realities of space-electronics PCB design and manufacturing directly into our generative engine. In this role, you will own end-to-end PCB design — schematic capture, stackup definition, high-speed and mixed-signal layout, signal and power integrity, fabrication and assembly readiness — for flight hardware, and translate that hard-won expertise into the constraints, heuristics, and feedback loops that let our AI agents design boards that can actually be built, qualified, and flown.

You will work at the intersection of PCB design, space-grade manufacturing, and AI — pairing your own hands-on board work with software development that captures DfM, DfA, and DfT considerations as code. This role is ideal for someone who has personally laid out flight boards, knows what fabricators and assembly houses actually need to see on a drawing package, and is excited to guide the team and write the software that lets an agent reason about those same trade-offs. You should be passionate about both leading a team and building this product: not just designing one more board, but multiplying your impact by encoding your judgment into a system that designs the next thousand.

You will be joining the Agentic Computational Engineering (ACE) team, a specialized group within our Advanced Technology Development organization. ACE is responsible for building Voyager’s Generative Engine – the AI-native platform that compresses complex hardware development cycles from years to days. We design agentic AI systems that pair deeply with physics simulation, test data, and modern manufacturing so that Design for Manufacturing (DfM), Design for Assembly (DfA), and Design for Test (DfT) are built into the very first line of code and the very first sketch of a design.

The position reports to the VP, AI & Autonomy and is part of the Technology and Advanced Development department based in Los Angeles, CA; Washington D.C; Seattle, WA.

This role is hybrid based in Los Angeles, CA; Washington D.C; Seattle, WA.

• Own the vision and execution of the PCB vertical of the Agentic Computational Engineering platform — defining how an agentic system should reason about end-to-end PCB design and manufacturing for space-grade flight electronics, and guiding the engineering team that implements it.
• Frame the problem space for the team: catalogue the design and manufacturing decisions a senior PCB engineer makes on a flight program (substrate and stackup, SI/PI, DfM/DfA/DfT, parts derating, fab and assembly liaison, qualification) and translate each into structured problems an agent can solve autonomously.
• Plan the PCB vertical's roadmap in lockstep with AI, simulation, manufacturing, and product leadership — sequencing capabilities, identifying high-leverage bets, and articulating clear success criteria for each agentic capability we ship.
• Educate the team continuously on space-electronics PCB design and manufacturing — running design-review walkthroughs, writing internal references, and turning your judgment into shared mental models the rest of the team can build against.
• Drive product taste for the PCB vertical: define what a great agent-generated design package looks like, what quality bar it must hit, and where the agent should defer to a human — so the team builds something that practicing PCB engineers actually trust.
• Lead testing and qualification of agent-generated designs — running design reviews, fabricating and assembling representative boards, and executing electrical, environmental (vibe, thermal, EMI/EMC), and radiation campaigns to evaluate real-world performance.
• Provide detailed, structured feedback to the team building the platform — turning every test, fab spin, and design review into specific, actionable signals that improve the agents, the constraint models, and the simulation tie-ins.
• Partner with fab houses, assembly houses, and component vendors to encode their real constraints — IPC class 3, NASA workmanship, lead times, parts availability, qualification artifacts — into the platform so generated designs are buildable on the first spin.
• Set the technical direction for AI-driven tooling in the PCB vertical (Python/C++ services, LLM-based agents, scripting), guiding engineers on how to decompose PCB-engineering judgment into agents that can make decisions autonomously and explain them.
• Represent the PCB vertical to Voyager hardware programs and external customers — communicating capabilities, limitations, and the roadmap with the credibility that comes from having designed flight hardware yourself.

In this role, the essential functions are:

If your experience aligns with our basic qualifications and you are inspired by our mission, we’d like to connect. If you don’t see the right role right now, Join Our Talent Community and stay connected as we continue to build what’s next. 

• 12+ years of hands-on PCB design experience for space, aerospace, defense, or other high-reliability electronics, including delivered flight or flight-equivalent hardware on programs you can speak to in depth.
• Demonstrated technical leadership of a PCB or hardware function — setting direction, mentoring engineers, owning quality, and being the person the rest of the team escalates to on hard design and manufacturing calls.
• End-to-end mastery of the PCB process — schematic capture, multi-layer stackup design, controlled-impedance and high-speed routing, mixed-signal and RF layout, SI/PI analysis, DfM/DfA/DfT, fab/assembly liaison, bring-up, and environmental/qualification testing — in Altium Designer or equivalent ECAD.
• Excellent product taste: a track record of deciding what to build, what quality bar to hold, and what to cut — and articulating those calls clearly to engineering, product, and program stakeholders.
• Strong communication and teaching ability — comfortable running design reviews, writing internal documentation, and educating non-PCB engineers (AI, software, simulation, manufacturing) on what matters and why.
• Strong programming skills in Python and/or C++, and demonstrated use of AI tools, LLMs, or scripting to automate engineering work — design reviews, BOM management, layout checks, parts-stress analysis, or data pipelines.
• Ability to define how an agentic system should reason about engineering problems — decomposing PCB design and manufacturing decisions into objectives, constraints, and feedback signals an autonomous agent can act on.
• Genuine passion for building this product: excited to lead a team that turns your hard-won PCB judgment into a generative engine designing the next thousand boards.
• Ability to obtain and maintain a U.S. Top Secret Security Clearance.

Preferred Qualifications: 

• Master's or PhD in Electrical Engineering or related discipline.
• Experience leading PCB design or hardware engineering at NASA centers, JPL, major space primes, or new-space companies; familiarity with PDR/CDR processes, NASA workmanship standards (NASA-STD-8739), SMC-S-016, MIL-STD-461G, WCCA/EPSA, and IPC class 3.
• Hands-on experience with FPGA/SoC-based single-board computers (e.g., Xilinx Ultrascale+ MPSoC, GR712, RTAX/RTG4), high-speed ADC/DAC layout, and RF front-ends across UHF through Ka-band.
• Experience defining or qualifying substrates and stackups (e.g., Rogers, Isola Tachyon/MT-40) against electrical, thermal, and radiation-environment requirements, and running radiation effects testing (TID, SEE, SEL, SEU).
• Familiarity with systems-engineering tooling (JAMA, DOORS, Jira) and EICD/requirements practices spanning box, slice, and board level.
• Track record of building or leading the build of internal tooling, design automation, or AI/LLM-based assistants that measurably improved PCB design or review throughput.
• Experience guiding software or AI engineers — translating engineering domain knowledge into specifications, evaluation criteria, and feedback that shape what gets built.
• Evidence of personal projects in electronics, robotics, or RF — the kind of work where you build the thing yourself for the love of it.

The good faith base salary range for this role is$225,000 - $290,000 at the time of this posting. Where you fall within the range depends on your experience, skills, and location. This range reflects base salary only and does not include benefits or bonus/incentive. This range may be adjusted in the future.

This position is incentive plan eligible.

Voyager offers a highly competitive total compensation package designed to support the well-being, growth, and success of our employees. Employees benefit from a flexible and comprehensive rewards program that supports both professional and personal well-being.  

• Flexible Time Off (FTO), empowering employees to take the time they need to recharge and maintain a healthy work-life balance

• Comprehensive medical, dental, and vision coverage for employees and their families, with a significant portion of premiums covered by the company and many benefits paid at 100% for employees
• Flexible, affordable gym memberships with 12,700+ options nationwide including 24 Hour Fitness, EoS Fitness, Crunch Fitness, Anytime Fitness, Blink Fitness, Chuze Fitness and more! No long-term contracts and FREE on-demand workout videos before you enroll

• 401(k) retirement plan with a 50% company match on contributions up to 8%, supporting long-term financial security

• Company wellness programs that support physical and mental well-being

• Additional voluntary benefits and employee support resources
• The opportunity to work alongside a highly talented team in an innovative, mission driven environment

Voyager is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law. 

Able to obtain and maintain a U.S. security clearance

Minority/Female/Disabled/Veteran 

The statements contained in this job description are intended to describe the general content and requirements for performance of this job. It is not intended to be an exhaustive list of all job duties, responsibilities, and requirements. This job description is not an employment agreement or contract. Management has the exclusive right to alter the scope of work within the framework of this job description at any time without prior notice. 

About the Role

The Cloud Inference team scales and optimizes Claude to serve the massive audiences of developers and enterprise companies across AWS, GCP, Azure, and future cloud service providers (CSPs). We own the end-to-end product of Claude on each cloud platform, from API integration and intelligent request routing to inference execution, capacity management, and day-to-day operations.

Our engineers are extremely high leverage: we simultaneously drive multiple major revenue streams while optimizing one of Anthropic's most precious resources: compute. As we expand to more cloud platforms, the complexity of managing inference efficiently across providers with different hardware, networking stacks, and operational models grows significantly. We need product-minded backend engineers who can navigate these platform differences, design the services and abstractions that work across providers, and make architectural decisions that keep us reliable and cost-effective at massive scale.

Your work will increase the scale at which our services operate, accelerate our ability to reliably launch new frontier models and innovative features to customers across all platforms, and ensure our LLMs meet rigorous safety, performance, and security standards.

What You'll Do

• Design, build, and own backend services and infrastructure that serve Claude across multiple CSPs, accounting for differences in compute hardware, networking, APIs, and operational models
• Work cross-functionally with internal inference, product API, systems, and security teams, among others, and with CSP partners to stand up the full serving stack on new cloud platforms, resolve operational issues, and influence provider roadmaps
• Build and evolve CI/CD automation systems, including validation and deployment pipelines, that reliably ship new model versions to millions of users across cloud platforms without regressions
• Design interfaces and tooling abstractions across CSPs that enable cost-effective inference management, scale across providers, and reduce per-platform complexity
• Contribute to capacity planning, autoscaling, and workload routing strategies that match supply with demand and direct requests to the most cost-effective accelerator and region
• Analyze observability data across providers to identify performance bottlenecks, cost anomalies, and regressions, and drive remediation based on real-world production workloads

You May Be a Good Fit If You:

• Have significant software engineering experience, with a strong background in high-performance, large-scale distributed systems serving millions of users
• Have experience building or operating services on at least one major cloud platform (AWS, GCP, or Azure), with exposure to Kubernetes, Infrastructure as Code, or container orchestration
• Are curious about LLM serving; prior inference or ML experience is not required
• Thrive in cross-functional collaboration with both internal teams and external partners
• Are a fast learner who can quickly ramp up on new technologies, hardware platforms, and provider ecosystems
• Are highly autonomous and take ownership of problems end-to-end, including work that falls outside your job description

Strong Candidates May Also Have Experience With

• Direct experience working with CSPs to scale infrastructure or products across multiple platforms, navigating differences in networking, security, privacy, billing, and managed service offerings
• Have experience working with external partners to align goals and deliver impact
• Hands-on experience with capacity management, cost optimization, or resource planning at scale across heterogeneous environments
• Solid understanding of multi-region deployments, geographic routing, and global traffic management
• Proficiency in Python or Rust

About the Role

We are looking for a Senior Solution Lead to join our high-performing Pre-Sales & Solution Strategy team. You will sit at the intersection of Sales, Delivery, Product, and Client Leadership, shaping the solutions we take to market and directly influencing multi-million-dollar outcomes.

This is not a “respond to the RFP and pray” role. This is a strategic, high-ownership, high-IQ seat where you:

• Shape the problem,
• Design the solution, and
• Influence how we win and deliver.

You will focus exclusively on large, complex opportunities valued at $1M+, where your problem-framing, technical depth, and storytelling materially impact win rates.

You will report to the Head of Pre-Sales & Solution Strategy and collaborate with a senior, globally distributed team across India, the US, and Europe.

Responsibilities:

What You’ll Own

1. Deal Shaping & Pre-Sales Architecture

• Translate ambiguous client goals into clear, compelling, technically credible solution architectures (Figma/Miro/Adobe)
• Lead discovery workshops, ask incisive questions, and define what a winning solution looks like—for the client and for us.
• Build decks, narratives, and pricing models that position us decisively above competitors. (Google/PP/Canva)
• Navigate seamlessly between C-level outcomes (business case, ROI, risk) and engineering deep dives (architecture, delivery approach, tradeoffs).
• Own the solution narrative end-to-end across EOI/RFI/RFP responses, orals, and executive briefings.
• Solution Estimating: Provide high level pricing estimates tied to value impact statements (ROI) for clients including software, hardware, cloud and tooling licensing for POC/MVP/Commercial models
  
  

2. Cross-Domain Solution Engineering

Own the solution across the full delivery lifecycle, spanning:

• Applications – modernization, greenfield engineering, platforms, integration
• Infrastructure – cloud infra, DevOps, SRE, infra automation
• Security – controls, IAM, governance, secure-by-design patterns
• Cloud – AWS / Azure / GCP architectures, migration strategies, optimization / FinOps
• Tooling- AI models, ISV licenses, tokens etc

You bring technical breadth with depth in at least one practice area and can credibly orchestrate end-to-end solutions.

A practical understanding of how AI cuts across these domains is essential, including:

• agentic automation across workflows and operations
• private AI stacks (RAG, governance, observability)
• model-integrated applications and copilots that augment existing systems

3. Go-To-Market & Productized Offerings

• Turn our capabilities into clear, differentiated, repeatable solutions and offerings.
• Collaborate with Product, Delivery, and Marketing to evolve our GTM playbooks and sales assets.
• Package reference architectures, POVs, and standard patterns based on real market demand.
• Capture learnings from deals and delivery to refine offerings and win themes.

4. Internal Collaboration & Leadership

• Partner closely with Sales on deal strategy, qualification, and pursuit plans.
• Align with Delivery Leaders to ensure proposed solutions are buildable, profitable, and differentiated.
• Contribute to sales enablement via reusable messaging, templates, and pricing frameworks.
• Act as a thought leader and mentor for junior solution engineers and architects.

What Success Looks Like

• You influence $6M+ in annual revenue through deals with TCV targets valued at $1M+.
• Stakeholders (Sales, Delivery, Clients) consistently rate your solutions as clear, differentiated, and client-aligned.
• Sales teams proactively pull you into strategic conversations because you “help deals close.”
• Delivery teams trust your architectures—and want to build them.
• You significantly enhance our GTM library with reusable assets, offerings, and standard patterns.
• Over time, you shape or lead 1–2 strategic offerings or solution themes for the company.

Who Thrives in This Role

We’re targeting top-tier pre-sales / solution engineering talent in India who demonstrate:

• Flexible thinking – can reshape a problem even when the client can’t articulate it clearly
• Structured reasoning – can break down complexity into options, tradeoffs, and recommendations
• Technical breadth + depth – strong grounding in apps, infra, security, and cloud, with a sharp view of how AI enhances each
• Storytelling ability – can communicate crisply to CXOs, procurement, and engineering teams
• Calm confidence – comfortable leading conversations amid ambiguity and pace
  Ownership mindset – thinks like an owner, not a vendor; cares about long-term value and delivery success

About You

The essentials:

• 7–12+ years in pre-sales engineering, solutions architecture, or consulting roles in IT services / SaaS / cloud / AI-led solutions
• Proven ability to influence or close $1M+ services deals (multi-tower or multi-year preferred)
• Hands-on understanding of services delivery, including SDLC, cloud migrations, modernization, architecture patterns, and infra operations
• Experience designing or positioning solutions with AI integration, agent workflows, automation, or model-enhanced apps (copilots, RAG systems, intelligent workflows)
• Ability to build defensible pricing models (T&M, fixed-price, managed services, outcome-based)
• Strong written and verbal communication skills in English; experienced presenting to senior stakeholders
• Comfortable working with distributed global teams across time zones

Not a must, but a plus:

• Hands-on experience with one or more major cloud providers (AWS, Azure, GCP)
• Familiarity with modern data and AI stacks (Snowflake, Databricks, vector DBs, LLM orchestration frameworks)
• Background in consulting-led environments (Big 4, global SIs, boutique consulting firms)
• Industry experience in BFSI, Retail, Manufacturing, Healthcare, or similar

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.  

LOCATION salary range

$150,000— $180,000 USD

#LI-REMOTE 

#LI-SDL1

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

What we do  

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

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

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

What you’ll do: 

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

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

Who you are: 

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

#LI-TP1

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

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

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

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

#LI-TP1

About the role:

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

Responsibilities:

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

You may be a good fit if you:

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

Strong candidates may also have:

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

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

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

About the Team

As a Senior+ Agentic Analytics Engineer at Opendoor, you will join the Data organization and help build something that doesn't exist at most companies: an Agentic Analytics team. This is a high-impact IC role at the intersection of data science, data engineering, and AI.

Opendoor has adopted a "Default to AI" philosophy—if AI can handle it, AI should handle it. We're not theorizing about AI transformation; we're shipping it.

Why This Role

Most analytics teams are stuck in reactive mode—fielding ad-hoc requests and building dashboards that go stale. We're building something different: AI systems that proactively tell leaders what they should focus on, why it matters, and what to do about it.

If you want to define what analytics looks like in an AI-first company, this is it.

What You'll Do

Build Proactive Intelligence Systems

• Design and deploy AI agents that monitor business performance and surface actionable insights without being asked

• Architect systems that shift analytics from "answering questions" to "anticipating needs"

• Create intelligent alerting that distinguishes signal from noise and recommends specific actions

Create AI-Powered Analytics Tools

• Develop natural language interfaces that let business leaders query data conversationally

• Build semantic layers that translate business concepts into data structures optimized for LLM reasoning

• Ship internal tools that transform how Opendoor makes decisions at every level

Own the Analytics-to-Action Pipeline

• Design data models that support automated analysis, pattern detection, and AI agent interactions

• Build workflows that connect insight generation to recommended actions

• Establish feedback loops that make our AI systems smarter over time

Drive Leverage Across the Business

• Identify high-value opportunities where AI can augment human decision-making

• Implement end-to-end solutions using Claude, custom agents, and modern AI tooling

• Measure impact rigorously—we care about decisions influenced, not dashboards built

We're Looking for Teammates Who Have

Technical Foundation

• 5+ years of experience in analytics, data science, or data engineering, with increasing scope and ownership

• Expert-level SQL with demonstrated ability to design complex data models and optimize for both human and AI consumption

• Strong Python proficiency for data engineering, automation, and AI agent development

• Experience with modern data warehouses (Snowflake, BigQuery, or similar) and the broader data stack (dbt, Airflow, etc.)

AI & Automation Expertise

• Hands-on experience building and deploying AI agents or LLM-powered applications in production

• Deep understanding of LLM capabilities, limitations, and prompt engineering best practices

• Experience architecting semantic layers or natural language interfaces for data access

• Proven ability to identify high-ROI automation opportunities and ship end-to-end solutions

Analytics & Business Acumen

• Track record of driving measurable business impact through analytics—not just producing analyses, but influencing decisions

• Strong analytical intuition—you know what questions matter before they're asked

• Experience translating ambiguous, cross-functional business problems into technical solutions

• History of operating autonomously and setting direction, not just executing on defined projects

Leadership & Influence

• Experience mentoring other analysts or engineers, formally or informally

• Demonstrated ability to influence senior stakeholders and drive alignment across teams

• Comfort operating in ambiguity and shaping strategy, not just responding to it

• Track record of building systems and processes that scale beyond yourself

Builder Mindset

• You ship products, not just dashboards 

• You'd rather build something useful in a week than something perfect in a quarter

• You measure success by business impact, not technical complexity

• You're energized by creating leverage—building once so others benefit forever

Bonus Points If You Have

• Experience in real estate, fintech, or marketplace businesses

• Background in marketing analytics, sales operations, product analytics, or pricing/economics

• History of building tools or platforms that replaced recurring analyst work

• Experience leading technical projects or small teams

About the Team

As a Senior+ Agentic Analytics Engineer at Opendoor, you will join the Data organization and help build something that doesn't exist at most companies: an Agentic Analytics team. This is a high-impact IC role at the intersection of data science, data engineering, and AI.

Opendoor has adopted a "Default to AI" philosophy—if AI can handle it, AI should handle it. We're not theorizing about AI transformation; we're shipping it.

Why This Role

Most analytics teams are stuck in reactive mode—fielding ad-hoc requests and building dashboards that go stale. We're building something different: AI systems that proactively tell leaders what they should focus on, why it matters, and what to do about it.

If you want to define what analytics looks like in an AI-first company, this is it.

What You'll Do

Build Proactive Intelligence Systems

• Design and deploy AI agents that monitor business performance and surface actionable insights without being asked

• Architect systems that shift analytics from "answering questions" to "anticipating needs"

• Create intelligent alerting that distinguishes signal from noise and recommends specific actions

Create AI-Powered Analytics Tools

• Develop natural language interfaces that let business leaders query data conversationally

• Build semantic layers that translate business concepts into data structures optimized for LLM reasoning

• Ship internal tools that transform how Opendoor makes decisions at every level

Own the Analytics-to-Action Pipeline

• Design data models that support automated analysis, pattern detection, and AI agent interactions

• Build workflows that connect insight generation to recommended actions

• Establish feedback loops that make our AI systems smarter over time

Drive Leverage Across the Business

• Identify high-value opportunities where AI can augment human decision-making

• Implement end-to-end solutions using Claude, custom agents, and modern AI tooling

• Measure impact rigorously—we care about decisions influenced, not dashboards built

We're Looking for Teammates Who Have

Technical Foundation

• 5+ years of experience in analytics, data science, or data engineering, with increasing scope and ownership

• Expert-level SQL with demonstrated ability to design complex data models and optimize for both human and AI consumption

• Strong Python proficiency for data engineering, automation, and AI agent development

• Experience with modern data warehouses (Snowflake, BigQuery, or similar) and the broader data stack (dbt, Airflow, etc.)

AI & Automation Expertise

• Hands-on experience building and deploying AI agents or LLM-powered applications in production

• Deep understanding of LLM capabilities, limitations, and prompt engineering best practices

• Experience architecting semantic layers or natural language interfaces for data access

• Proven ability to identify high-ROI automation opportunities and ship end-to-end solutions

Analytics & Business Acumen

• Track record of driving measurable business impact through analytics—not just producing analyses, but influencing decisions

• Strong analytical intuition—you know what questions matter before they're asked

• Experience translating ambiguous, cross-functional business problems into technical solutions

• History of operating autonomously and setting direction, not just executing on defined projects

Leadership & Influence

• Experience mentoring other analysts or engineers, formally or informally

• Demonstrated ability to influence senior stakeholders and drive alignment across teams

• Comfort operating in ambiguity and shaping strategy, not just responding to it

• Track record of building systems and processes that scale beyond yourself

Builder Mindset

• You ship products, not just dashboards 

• You'd rather build something useful in a week than something perfect in a quarter

• You measure success by business impact, not technical complexity

• You're energized by creating leverage—building once so others benefit forever

Bonus Points If You Have

• Experience in real estate, fintech, or marketplace businesses

• Background in marketing analytics, sales operations, product analytics, or pricing/economics

• History of building tools or platforms that replaced recurring analyst work

• Experience leading technical projects or small teams

• Own end-to-end delivery of AI product features
  Lead the design and implementation of complex features—from initial concept through production—ensuring high quality and strong user impact.
• Drive system design for AI-backed experiences
  Architect systems that orchestrate LLMs, retrieval, and structured data, making thoughtful tradeoffs between flexibility, reliability, and performance.
• Elevate product quality through iteration and evaluation
  Establish and improve feedback loops (evaluation frameworks, user signals, experimentation) to systematically improve AI output quality.
• Lead technical direction within a product area
  Break down ambiguous problems, define approaches, and guide execution across multiple engineers.
• Mentor and raise the engineering bar
  Provide guidance on code quality, system design, and product thinking; help less experienced engineers operate more effectively in an AI-driven environment.
• Accelerate team velocity through AI-assisted development
  Model effective use of modern AI tools to improve iteration speed, code quality, and overall team productivity.

• Has 5+ years of experience building and scaling product-facing systems, with a track record of owning complex features or product areas end-to-end
• Writes clean, maintainable code (Python preferred) and makes strong architecture and design decisions across a modern web stack
• Brings a high bar for product quality, not just system correctness — consistently asks whether what's being built actually serves users well
• Has experience working with AI/LLM-powered systems, or can ramp quickly and contribute meaningfully to shaping their behavior in production
• Drives projects from idea → production with strong ownership, and helps others do the same through mentorship and technical leadership
• Thrives in ambiguous, fast-moving environments and can set technical direction, not just execute within it

• Experience building or experimenting with LLM-powered features (prompting, evaluation, RAG, etc.)
• Experience designing systems that balance latency, cost, and quality
• Exposure to user feedback loops, experimentation, or evaluation frameworks

About Otter.ai 

We are in the business of shaping the future of work. Our mission is to make conversations more valuable.

With over 1B meetings transcribed, Otter.ai is the world’s leading tool for meeting transcription, summarization, and collaboration. Using artificial intelligence, Otter generates real-time automated meeting notes, summaries, and other insights from in-person and virtual meetings - turning meetings into accessible, collaborative, and actionable data that can be shared across teams and organizations. The company is backed by early investors in Google, DeepMind, Zoom, and Tesla.

Otter.ai is an equal opportunity employer. We proudly celebrate diversity and are committed to building an inclusive and accessible workplace.  We provide reasonable accommodations for qualified applicants throughout the hiring process.  

Accessibility & Accommodations

Otter.ai is committed to providing reasonable accommodations for candidates with disabilities in our hiring process.  If you need assistance or an accommodation during any stage of the recruitment process, please contact hr@otter.ai at least 3 business days before your interview.

*Otter.ai does not accept unsolicited resumes from 3rd party recruitment agencies without a written agreement in place for permanent placements. Any resume or other candidate information submitted outside of established candidate submission guidelines (including through our website or via email to any Otter.ai employee) and without a written agreement otherwise will be deemed to be our sole property, and no fee will be paid should we hire the candidate.

Salary range

Salary Range: $185,000 to $230,000 USD per year.

This salary range represents the low and high end of the estimated salary range for this position. The actual base salary offered for the role is dependent on several factors. Our base salary is just one component of a comprehensive total rewards package.

#LI-Hybrid

About the Role:

As the Enterprise Applications AI Architect, you will lead the integration of AI and automation across Gusto’s enterprise applications ecosystem, transforming how internal systems connect, communicate, and operate. Sitting within the IT and Enterprise Applications organization, you will partner closely with Product, Engineering, Finance, People Tech, and Operations to bridge business needs with AI driven solutions. You will act as the connector between business requirements and AI frameworks, designing Model Context Protocols (MCPs) and AI agents that make enterprise workflows smarter, faster, and more autonomous. In line with Gusto’s FY26 Enterprise Systems strategy, you will help shift our ERP and Finance systems from reactive workflows to predictive, context aware, and self improving platforms, while ensuring security, compliance, and measurable impact. This role combines hands-on technical execution with strategic systems thinking, using integration fluency, AI literacy, and business empathy to create the connective tissue that allows AI to seamlessly augment enterprise operations.

About the Team:

This role will report to the Enterprise AIT team, a group focused on driving the intelligent transformation of Gusto’s enterprise systems. The Enterprise AIT team is responsible for integrating AI, automation, and advanced analytics across our internal applications ecosystem to improve scalability, efficiency, and decision-making. Partnering closely with Finance, Business Ops, IT, and Security, the team enables Gusto’s enterprise systems to become smarter, more predictive, and more adaptive. This is a new role, designed to expand the team’s capacity to operationalize AI within enterprise workflows and support Gusto’s broader Enterprise Systems strategy.

Here’s what you’ll do day-to-day:

• Translate business needs into AI workflows by partnering with Finance and Business Operations teams to identify automation opportunities and design agentic workflows that improve decision making and reduce manual effort.
• Develop and maintain Model Context Protocols (MCPs) that securely and reliably connect enterprise systems such as NetSuite, Zuora, and Jira to AI agents, with clear documentation and optimization.
• Create and manage intelligent agents that execute or augment core enterprise processes such as onboarding, billing support, and compliance monitoring using large language models and orchestration frameworks.
• Govern the full lifecycle of MCPs and agents, ensuring adherence to enterprise data governance, privacy, and security standards, including SOX compliance, auditability, and appropriate access controls.
• Measure and optimize impact by defining and tracking KPIs such as automation adoption, efficiency gains, agent accuracy, reliability, and cost performance, and using those insights to guide iteration.
• Enable and influence the organization by partnering with IT, Security, and business stakeholders to build reusable AI frameworks, coach teams on safe and effective AI driven workflows, and champion AI first practices across day to day operations.

Here’s what we're looking for:

• 8+ years in Business Systems Analysis, Enterprise Applications, or Automation roles, with a track record of delivering impact in complex environments.
• Demonstrated experience building and maintaining integrations across systems such as Jira, NetSuite, or similar, with a strong grasp of APIs, JSON, and RESTful service design.
• Hands-on knowledge of AI agent frameworks (for example LangChain, CrewAI, Semantic Kernel, MCP) and experience designing or maintaining Model Context Protocols or equivalent frameworks.
• Familiarity with leading LLM platforms (OpenAI, Anthropic, Gemini etc.) and practical experience with prompt engineering.
• Proficiency in Python or JavaScript for automation, orchestration, and building modular, scalable AI workflows that translate complex requirements into executable solutions.
• Strong documentation, analytical, and stakeholder communication skills, with the ability to clearly explain tradeoffs and align technical solutions with business needs.
• Passion for building secure, compliant, and explainable AI systems, embedding risk, privacy, and compliance considerations (including SOX and audit controls) into every solution, with a growth mindset and focus on clarity, iteration, and measurable outcomes.

Our cash compensation amount for this role is targeted at $150,000-$165,000 /yr in Denver & most remote locations, and $185,000-$205,000 /yr for San Francisco, Seattle & New York. Final offer amounts are determined by multiple factors, including candidate experience and expertise, and may vary from the amounts listed above.

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

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.

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 Design at Gusto 

Design at Gusto is made up of over 80 creative, collaborative people who care deeply about our mission to empower small businesses and their employees. We're a cross-functional group that is always looking for opportunities to build understanding and empathy for the people who use Gusto. We don't care much about swim lanes and though we care deeply about quality and craft, we are never precious about it. We work closely with cross-functional partners in Product, Engineering, Data, and Marketing to design, build, and ship experiences that make a real difference. We believe great design can make hard things possible, even delightful.

We are building an AI-native design organization — and we mean that seriously. We're looking for designers who are already working this way: using AI to prototype ideas quickly, shorten customer feedback loops, and ship quality UX directly to customers. This isn't a future aspiration — it's how we work now, and it's changing what the design role looks like at Gusto and across the industry.

About the role:

We’re hiring a Principal Product Designer to lead AI design across Gusto.

This is one of the most senior individual contributor design roles at the company. You’ll define how AI works, behaves, and earns trust across the Gusto platform – starting with Gus, our AI conversational assistant, and expanding into AI-powered workflows embedded in payroll, benefits, HR, and beyond. You’ll shape the interaction model, UX principles, and product direction for AI across Gusto. You will work with senior Product and Engineering leaders to define our AI portfolio. You will develop important AI features that customers will consider and you’ll ship high-impact, customer-facing AI capabilities that help our customers get their work done faster and more effectively, while building their trust in Gusto. These features will help customers finish their tasks faster and build their trust in Gusto.

This role is both strategic and hands-on. We’re looking for someone who can set a long-term UX vision for AI and turn it into real, shipped product that meaningfully improves how small businesses get work done.

Here’s what you’ll do day-to-day:

• Define and evolve the UX vision for our Gus conversational assistant and AI experiences across the Gusto platform.
• Lead and ship Tier 1 AI initiatives from early concept through launch and iteration.
• Design full AI-powered workflows – shaping how users provide input, how model outputs are validated and acted on, and how the experience handles risk, uncertainty, and failure.
• Partner closely with AI Product and Engineering leaders to translate complex technical constraints into intuitive, credible user experiences.
• Establish scalable AI interaction patterns and design principles that teams across Gusto can adopt.
• Write and iterate on prompts in collaboration with engineering, PM, and content design.
• Use AI tooling to accelerate exploration and prototyping, customer feedback loops, and shipping to customers.
• Mentor designers on the AI team and coach designers across Gusto who are shipping AI features.
• Advocate for high-quality, responsible AI experiences across Design and R&D.

Here’s what we're looking for:

• Proven AI product impact: You’ve shipped LLM-driven product experiences to production and can demonstrate measurable impact on adoption, efficiency, or user trust.
• Systems-level thinking: You’ve designed complete AI workflows – not just chat interfaces – and can speak fluently about failure modes, guardrails, user control, and transparency.
• Strategic product influence: You’ve defined UX direction at a portfolio or company level and influenced roadmap, scope, and sequencing decisions in partnership with senior PM and Engineering leaders.
• Technical fluency: You’re comfortable collaborating with highly technical AI engineers. You understand concepts like retrieval, context management, latency, and model reliability, and can translate them into robust UX decisions.
• Builder mindset: You ship. You prototype. You iterate. You’re not interested in defining principles without turning them into real customer impact.
• Organizational leadership: You have enhanced team work quality. You achieved this by coaching team members, setting new standards, and building solid partnerships across different functions.

Compensation Details

At Gusto, we strive to provide rewards that empower employees to achieve their financial and personal goals. We offer competitive compensation packages with a strong emphasis on equity based compensation (ownership in Gusto). To learn more about Gusto’s compensation philosophy and benefits offerings please view our Total Rewards Approach page.

Our cash compensation range for this role is $204,000/yr to $238,000/yr in Denver & most remote locations, and $240,000/yr to $280,000/yr in San Francisco, Seattle & New York. Final offer amounts are determined by multiple factors, including candidate experience and expertise, and may vary from the amounts listed above.

Hudson River Trading (HRT) is hiring an AI Researcher to join the HAIL team. HAIL (HRT AI Labs) is the team at HRT responsible for developing and maintaining our most powerful models, which are used by our trading teams to drive a significant fraction of our trading. We are building and deploying "foundation models for markets", that ingest and train on vast amounts of market data, to make predictions about future market state. We are seeking experienced AI researchers to join our team to accelerate our efforts.

Researchers have great independence to pursue the research directions they think would be most impactful as part of a small focused team with minimal bureaucracy. They are enabled by state-of-the-art research clusters with very high GPU-to-researcher ratios, and supported by excellent engineering, hardware, and systems teams to realize their vision. Your work will be directly, clearly, highly impactful on the business, and it will be challenging: this is a field with no easy or obvious solutions. You'll be responsible for improving every part of our models: from featurization of data, to architecture design, to training dynamics, to how trading decisions are made.

Qualifications

• Must have two or more years work experience in deep learning research, for any domain: robotics, biology, chemistry, physics, audio, video, etc.
• Experience translating methods between areas of application is highly valued.
• LLM experience is valuable, but not necessary.
• Strong engineering skills valued, especially any of: GPU kernel development, lower-level Pytorch/JAX development, intermediate C++, FPGA/ASIC experience, HPC experience.

The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. 

This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package which includes medical, dental, vision, basic life insurance, and enrollment in our company’s retirement savings plans. Employees will receive sick and parental leave, as well as other paid time off (including 20 vacation days and 10 paid holidays in the US). Please note that benefits and time off policies will vary across non-US locations.

Responsibilities:

• Designing and implementing from scratch new information architecture strategies
• Performing finetuning and reinforcement learning to teach language models how to interact with new information architectures
• Building “hard” knowledge base eval sets to help identify failure modes of how language models work with external data
• Designing and evaluating advanced agentic search capabilities.

You may be a good fit if you:

• Are a very experienced Python programmer who can quickly produce reliable, high quality code that your teammates love using
• Have good machine learning research experience 
• Have experience developing software that utilizes Large Language Models such as Claude
• Are results-oriented, with a bias towards flexibility and impact
• Pick up slack, even if it goes outside your job description
• Enjoy pair programming (we love to pair!)
• Want to partner with world-class ML researchers to develop new LLM capabilities
• Care about the societal impacts of your work
• Have clear written and verbal communication

Strong candidates will also have experience with:

• Collaborating with product teams to quickly prototype and deliver innovative solutions
• Building complex agentic systems that utilize LLMs
• Developing scalable distributed information retrieval systems, such as search engines, knowledge graphs, RAG, indexing, ranking, query understanding, and distributed data processing

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

Your Role:

Tenable is seeking an experienced Pre-Sales Engineer to own and drive the Business and Technical aspects of strategic Enterprise selling in your assigned region. You will be partnering with Enterprise Territory Managers and a strong team of peers to differentiate the Tenable solutions from our competitors, create lasting customers by positioning unique business values they are looking for and most importantly, create raving fans of Tenable throughout your area of influence.

Your Opportunity:

• Deliver compelling technical presentations and live demonstrations of Tenable Enterprise products
• Manage enterprise software trials and Proof of Concept evaluations, mapping unique business values with customer business objectives
• Answer technical questions and provide consultative guidance on security best practices, compliance frameworks, and risk management
• Apply advanced technical skills to demonstrate the value and impact of Tenable’s solutions in solving real-world customer challenges
• Maintain and strengthen relationships with existing customers, while identifying and cultivating new strategic opportunities
• Present thought leadership content and represent Tenable at industry events, executive briefings, and customer-facing sessions
• Leverage strategic technical selling skills to engage key stakeholders, from engineers to CISOs, and influence decision-making
• Travel as needed (typically around 50%) to support key customer engagements, critical sales opportunities, and high-impact cybersecurity events
• Collaborate cross-functionally with product management and engineering to surface customer feedback and prioritize critical customer use cases
• Help shape future innovations by identifying gaps and contributing ideas for new product features and capabilities
• Deliver clear status reports for Proofs of Value (POVs) and active opportunities; this data is mission-critical for forecasting business health and ensuring alignment with territory and organizational growth goals
• Meet with prospective clients to discover what their biggest security challenges and highest priority business drivers are

What You'll Need:

• 5+ years of experience in a customer-facing technical sales role, with a demonstrated track record as a trusted and successful sales engineer
• Proven ability to lead and win technical proof-of-value (PoV) engagements with strategic enterprise customers
• A customer-centric mindset, with a relentless focus on delivering business value and building long-term relationships
• Recognized thought leadership in cyber security, including experience in public speaking and industry engagement
• Strong communication skills with the ability to tailor and deliver impactful presentations to diverse audiences, including engineers, security professionals, and executive stakeholders
• A collaborative, team-oriented approach, committed to knowledge-sharing and cross-functional success, while proudly representing our One Tenable team culture
• Exceptional Situational and Self-Awareness, with the high emotional intelligence (EQ) required to navigate complex stakeholder dynamics, adapt communication styles in real-time, and maintain a grounded, professional presence during high-pressure technical demonstrations

And Ideally:

• 5+ years of Sales Engineering experience with a focus on vulnerability management, cloud security, Operational Technology or complex enterprise SaaS environments
• Core Network Security & TCP/IP Foundations, including an understanding of the OSI model, packet analysis, and other advanced network security concepts
• Vulnerability Management Expertise, with hands-on experience using Nessus and other industry-standard network security scanning tools to identify, validate, and prioritize vulnerabilities across hybrid environments
• Experience with securing modern Cloud Infrastructure like AWS, Azure, and Google Cloud
• Basic understanding of Container Security, specifically securing Docker and Kubernetes (K8s) environments
• AI Security Knowledge, including the ability to identify and mitigate risks that LLM’s, and agents bring to businesses
• Basic Understanding of Identity and Access Management (IAM), including its critical role as the modern security perimeter and how to manage user and service permissions across cloud environments
• Automation & DevSecOps Mindset, with the ability to leverage Python SDKs, REST/GraphQL APIs, Terraform, and more
• Strategic Compliance Knowledge, mapping technical findings to frameworks like CIS, FISMA, PCI, and emerging AI-specific regulations (e.g., NIST AI RMF)
• Strong Academic & Professional Credentials, including a BS in Computer Science (or equivalent) and certifications such as CISSP, AWS Solutions Architect, or CKA (Certified Kubernetes Administrator)
• Obtain a basic knowledge and use of the command line, and is familiar with and able to demonstrate proficient use of our API

#LI-MS1

We are seeking a Machine Learning Engineer to join our team at MORSE.  You will play a pivotal role in designing, implementing, and managing complex ML algorithms and systems, with a focus on computer vision (CV) and other types of data. You will be responsible for acquiring truth data, integrating algorithms, testing algorithms, combining algorithms, reviewing literature to stay on top of the latest-and-greatest methods, analyzing data from field tests, and developing advanced algorithms.  MORSE’s AI & ML work crosses modalities, and experience or interest in the fields of Large Language Models (LLM), audio analysis, computer vision, and advanced reasoning is a plus. You will work with MORSE’s current team of engineers to transition algorithms to production, which may run on on-prem servers, on the cloud, or on a real-time embedded system. You will be part of our team working to accelerate our US National Security customers abilities to use natural language processing capabilities in mission-critical environments. 

Responsibilities: 

• Develop, fine-tune, train, and optimize Computer Vision algorithms processing tasks such as object detection and tracking.  

• Use MLOps tools for efficient experiment tracking, data management, and reproducibility 

• Write robust, efficient, and maintainable code 

• Track the latest advancements with machine learning research to bring new techniques and methodologies to MORSE 

• Conduct experiments and perform rigorous evaluations to assess the effectiveness and efficiency of CV models 

Skills and Requirements: 

• US CITIZENSHIP REQUIRED and the ability to obtain a U.S. Security Clearance 

• Masters or Ph.D. in Computer Science, Computer Engineering, Data Science, Aerospace, Mathematics, Physics, or related field 

• Proven experience in applying CV models, techniques, frameworks, and libraries to implement and fine-tune models 

• Proven experience testing and validating the performance of AI technologies in real-world applications 

• Proficiency in Python  

• Experience with cloud platforms (AWS and Azure)  

• Experience with Docker 

• Experience with MLOps tools such as Airflow, MLFlow, AimStack, etc. 

• Exceptional communication skills and the ability to work well with customers 

• Understanding of Department of Defense requirements and standards is a plus 

• Define system architecture for AI-native product surfaces
  Design foundational systems (generation pipelines, data models, evaluation frameworks) that power multiple product areas.
• Drive cross-team technical strategy
  Lead initiatives that span product, AI, and infrastructure teams, ensuring alignment on architecture and execution.
• Establish best practices for AI product engineering
  Set standards for how we build with AI—covering areas like evaluation, reliability, iteration loops, and system design.
• Translate ambiguity into scalable systems and product direction
  Take loosely defined opportunities and turn them into clear technical approaches and execution plans.
• Raise the bar across the organization
  Influence engineering quality, system design, and product thinking beyond your immediate team.
• Shape how AI accelerates engineering velocity
  Drive adoption and best practices for AI-assisted development, improving how teams design, build, and iterate on product.

• Has 10+ years of experience building and scaling complex systems
• Has a strong track record of owning technical and product direction for large or ambiguous problem spaces
• Demonstrates deep expertise in system design, especially in data-intensive or distributed systems
• Has experience leading cross-team initiatives and influencing without direct authority
• Brings strong product intuition and can balance user experience, system constraints, and business impact
• Is comfortable operating at a high level of ambiguity and defining both the problem and the solution

• Experience building or experimenting with LLM-powered features (prompting, evaluation, RAG, etc.)
• Experience designing systems that balance latency, cost, and quality
• Exposure to user feedback loops, experimentation, or evaluation frameworks

About Otter.ai 

We are in the business of shaping the future of work. Our mission is to make conversations more valuable.

With over 1B meetings transcribed, Otter.ai is the world’s leading tool for meeting transcription, summarization, and collaboration. Using artificial intelligence, Otter generates real-time automated meeting notes, summaries, and other insights from in-person and virtual meetings - turning meetings into accessible, collaborative, and actionable data that can be shared across teams and organizations. The company is backed by early investors in Google, DeepMind, Zoom, and Tesla.

Otter.ai is an equal opportunity employer. We proudly celebrate diversity and are committed to building an inclusive and accessible workplace.  We provide reasonable accommodations for qualified applicants throughout the hiring process.  

Accessibility & Accommodations

Otter.ai is committed to providing reasonable accommodations for candidates with disabilities in our hiring process.  If you need assistance or an accommodation during any stage of the recruitment process, please contact hr@otter.ai at least 3 business days before your interview.

*Otter.ai does not accept unsolicited resumes from 3rd party recruitment agencies without a written agreement in place for permanent placements. Any resume or other candidate information submitted outside of established candidate submission guidelines (including through our website or via email to any Otter.ai employee) and without a written agreement otherwise will be deemed to be our sole property, and no fee will be paid should we hire the candidate.

Salary range

Salary Range: $210,000 to $275,000 USD per year.

This salary range represents the low and high end of the estimated salary range for this position. The actual base salary offered for the role is dependent on several factors. Our base salary is just one component of a comprehensive total rewards package.

#LI-Hybrid

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

With over half a billion rides and counting, Lyft is solving hard problems at scale, leveraging AI and Machine Learning to better serve our customers. The Artificial Intelligence, Machine Learning, and Operations Research Platforms team (AIMLOR) is seeking a Senior Machine Learning Engineer to focus on building AI Platform components enabling critical AI applications across Lyft. Expertise with GenAI and platform building is a core requirement for this role. In this role, you will contribute to our platform which supports real-time, online, and offline AI and ML model execution, development, and iteration. You will work with a team of highly motivated Machine Learning and Software Engineers on challenging problems, defining solutions to directly impact systems across the entire business.

If you are interested in building an AI Platform at scale, with applications across each facet of the company, we are searching for you.

If you are a creative and critical thinker with experience in AI and machine learning systems, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you.

Responsibilities:

• Contribute to the roadmap and architecture based on technology and business needs
• Write well-crafted, well-tested, readable, maintainable code
• Have a good grasp and ability to explain the various tradeoffs made in decisions
• Participate in code reviews to ensure code quality and distribute knowledge 
• Build features from tech specification to positive execution
• Incorporate considerations for business context and failure modes in your work
• Proactively participate in resolving ongoing incidents 
• Unblock, support, effectively communicate, and obtain buy-in within your team to achieve results
• Share your knowledge by giving brown bags and tech talks

Experience:

• BSc/MSc in Computer Engineering, Computer Science, Machine Learning related field or relevant work experience
• 5+ years of ML engineering experience working in any of these stacks: Python, GO, Java, etc.
• Experience with ML serving/training/deployment infrastructure; familiarity with cloud providers (e.g. AWS, Azure, Google Cloud); familiarity with GenAI ecosystem: LLMs, prompt engineering, MCP, RAG; hands-on experience with LLM fine-tuning techniques and frameworks (e.g. PEFT, LoRA); knowledge on deploying self-hosted LLMs (e.g. Llama, Mistral) for specialized tasks
• Experience with GenAI/LLM infrastructure, agent frameworks (e.g. LangChain, LangGraph); MLOps tooling (MLflow, Airflow)
• Preferred: Experience with AI assisted coding such as Cursor or Claude Code

Benefits:

• Great medical, dental, and vision insurance options with additional programs available when enrolled
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• 401(k) plan with company match to help save for your future
• In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Subsidized commuter benefits
• Monthly Lyft credits and complimentary Lyft Pink membership

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the San Francisco area is $162,800 - $203,500, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

With over half a billion rides and counting, Lyft is solving hard problems at scale, leveraging AI and Machine Learning to better serve our customers. The Artificial Intelligence, Machine Learning, and Operations Research Platforms team (AIMLOR) is seeking a Senior Machine Learning Engineer to focus on building AI Platform components enabling critical AI applications across Lyft. Expertise with GenAI and platform building is a core requirement for this role. In this role, you will contribute to our platform which supports real-time, online, and offline AI and ML model execution, development, and iteration. You will work with a team of highly motivated Machine Learning and Software Engineers on challenging problems, defining solutions to directly impact systems across the entire business.

If you are interested in building an AI Platform at scale, with applications across each facet of the company, we are searching for you.

If you are a creative and critical thinker with experience in AI and machine learning systems, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you.

Responsibilities:

• Contribute to the roadmap and architecture based on technology and business needs
• Write well-crafted, well-tested, readable, maintainable code
• Have a good grasp and ability to explain the various tradeoffs made in decisions
• Participate in code reviews to ensure code quality and distribute knowledge 
• Build features from tech specification to positive execution
• Incorporate considerations for business context and failure modes in your work
• Proactively participate in resolving ongoing incidents 
• Unblock, support, effectively communicate, and obtain buy-in within your team to achieve results
• Share your knowledge by giving brown bags and tech talks

Experience:

• BSc/MSc in Computer Engineering, Computer Science, Machine Learning related field or relevant work experience
• 5+ years of ML engineering experience working in any of these stacks: Python, GO, Java, etc.
• Experience with ML serving/training/deployment infrastructure; familiarity with cloud providers (e.g. AWS, Azure, Google Cloud); familiarity with GenAI ecosystem: LLMs, prompt engineering, MCP, RAG; hands-on experience with LLM fine-tuning techniques and frameworks (e.g. PEFT, LoRA); knowledge on deploying self-hosted LLMs (e.g. Llama, Mistral) for specialized tasks
• Experience with GenAI/LLM infrastructure, agent frameworks (e.g. LangChain, LangGraph); MLOps tooling (MLflow, Airflow)
• Preferred: Experience with AI assisted coding such as Cursor or Claude Code

Benefits:

• Great medical, dental, and vision insurance options with additional programs available when enrolled
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• 401(k) plan with company match to help save for your future
• In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Subsidized commuter benefits
• Monthly Lyft credits and complimentary Lyft Pink membership

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the Seattle area is $149,780 - $187,220, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

DigitalOcean is expanding its AI Infrastructure layer to support the next generation of AI-driven applications.

We are seeking a Senior Engineer 2 to play a key role in our AI Infrastructure Control Plane team. This team's mission is to orchestrate and operate compute fleet, storage and networking for running AI workloads - inference, training, fine-tuning - at scale. In this high-impact role, you will be a primary technical architect and leader, responsible for building the foundational control plane services that power our large Gen AI model hosting infrastructure.

This is a hands-on role, requiring you to be able to develop high quality software while availing of all the productivity boosts granted by the latest AI coding agents. You will bridge the gap between high-scale distributed systems and specialized AI inference orchestration to ensure our global platform remains simple, reliable, and accessible for developers building the next generation of AI applications.

What You’ll Do:

• Architectural Leadership: Drive the design and development of distributed services within our AI Infrastructure ecosystem, including complex orchestration for LLM inference and hosting services. Your focus will be the control plane orchestration of compute, networking, and storage for AI workloads.
• System Design: Create, refine, and assess system design proposals for our high-scale, multi-tenant inference cloud ecosystem, ensuring they meet rigorous standards for availability and resiliency.
• Operational Excellence: Lead the operational strategy for critical services, defining SLOs and leveraging advanced observability to maintain platform health in a high-scale environment.
• Cross-Functional Collaboration: Partner deeply with Product Management, TPMs, and Engineering Management peers to align technical roadmaps with business priorities.
• Strategic Growth: Work on new architecture initiatives that enable fleet optimization and help evolve DigitalOcean into a market leader for AI-native networking and infrastructure.

What You’ll Bring to DigitalOcean:

• Distributed Systems Mastery: Deep experience with distributed and cloud services, including messaging systems, databases, and infrastructure as code, observability, and security.
• Cloud Infrastructure Expertise: Advanced knowledge of cloud networking (VPCs, Load Balancers), containerization (Kubernetes), and cloud storage (block, object, NFS). Deep networking software experience (VLAN, RDMA, Ethernet, L3-L7 network protocols, etc) would be a plus.
• AI/ML Domain Knowledge: Proven experience building AI/ML products, specifically focusing on Gen AI platforms, LLM hosting, and inference workflows.
• Operational Track Record: Significant experience running customer-facing, high-availability services across multiple regions.
• Open Source Engagement: Experience integrating and building with open-source software and a bias for technical ownership.
• Software Engineering: Expert proficiency in GoLang or Python and familiarity with gRPC for service-to-service communication.

Compensation Range: 

• $139,200.00 - $174,000.00

*This is a hybrid role

JR: 2026-7623

#LI-Hybrid

DigitalOcean is expanding its AI Infrastructure layer to support the next generation of AI-driven applications.

We are seeking a Senior Engineer 2 to play a key role in our AI Infrastructure Control Plane team. This team's mission is to orchestrate and operate compute fleet, storage and networking for running AI workloads - inference, training, fine-tuning - at scale. In this high-impact role, you will be a primary technical architect and leader, responsible for building the foundational control plane services that power our large Gen AI model hosting infrastructure.

This is a hands-on role, requiring you to be able to develop high quality software while availing of all the productivity boosts granted by the latest AI coding agents. You will bridge the gap between high-scale distributed systems and specialized AI inference orchestration to ensure our global platform remains simple, reliable, and accessible for developers building the next generation of AI applications.

What You’ll Do:

• Architectural Leadership: Drive the design and development of distributed services within our AI Infrastructure ecosystem, including complex orchestration for LLM inference and hosting services. Your focus will be the control plane orchestration of compute, networking, and storage for AI workloads.
• System Design: Create, refine, and assess system design proposals for our high-scale, multi-tenant inference cloud ecosystem, ensuring they meet rigorous standards for availability and resiliency.
• Operational Excellence: Lead the operational strategy for critical services, defining SLOs and leveraging advanced observability to maintain platform health in a high-scale environment.
• Cross-Functional Collaboration: Partner deeply with Product Management, TPMs, and Engineering Management peers to align technical roadmaps with business priorities.
• Strategic Growth: Work on new architecture initiatives that enable fleet optimization and help evolve DigitalOcean into a market leader for AI-native networking and infrastructure.

What You’ll Bring to DigitalOcean:

• Distributed Systems Mastery: Deep experience with distributed and cloud services, including messaging systems, databases, and infrastructure as code, observability, and security.
• Cloud Infrastructure Expertise: Advanced knowledge of cloud networking (VPCs, Load Balancers), containerization (Kubernetes), and cloud storage (block, object, NFS). Deep networking software experience (VLAN, RDMA, Ethernet, L3-L7 network protocols, etc) would be a plus.
• AI/ML Domain Knowledge: Proven experience building AI/ML products, specifically focusing on Gen AI platforms, LLM hosting, and inference workflows.
• Operational Track Record: Significant experience running customer-facing, high-availability services across multiple regions.
• Open Source Engagement: Experience integrating and building with open-source software and a bias for technical ownership.
• Software Engineering: Expert proficiency in GoLang or Python and familiarity with gRPC for service-to-service communication.

Compensation Range: 

• $139,200.00 - $174,000.00

*This is a remote role

JR: 2026-7623

#LI-Remote