Staff AI Engineer, Strava
$260-280k
Offers Equity
3 days a week in office
Social network for tracking run and cycle routes
Be an early applicant
Social network for tracking run and cycle routes
501-1000 employees
Be an early applicant
$260-280k
Offers Equity
3 days a week in office
501-1000 employees
Company mission
To create the most committed, close, and engaged athlete community on the internet.
Role
Who you are
- 5+ years of experience building and operating complex, production AI or backend systems at scale, with a track record of decomposing large technical problems into well-scoped execution across teams
- Demonstrated experience building AI platform tooling or developer-facing infrastructure ideally for LLM or ML systems with a strong instinct for API design, versioning, and self-serve patterns
- Hands-on experience building with large language models in production: agentic workflows, prompt and context engineering, RAG architectures, embedding pipelines, fine-tuning workflows, or LLM evaluation frameworks and tools like Langchain
- Proficiency in search systems (Elasticsearch/OpenSearch, Vector Search, etc)
- Proficiency in backend service development on cloud environments (AWS preferred), using Python, Go. Solid understanding of distributed systems and containerized infrastructure (Kubernetes, Docker)
- Strong technical leadership: ability to lead multi-team projects, define technical direction, and grow engineers at multiple levels
- Deep curiosity about the evolving GenAI landscape: model capabilities, agent frameworks, multimodal systems: and strong judgment on where and how to apply them to real product problems
- Strong communication and collaboration skills, with the ability to align cross-functional partners around technical direction and build organizational trust in the platforms your team ships
What the job involves
- We are looking for a Staff AI Engineer to join the GenAI + Discovery Platform team at Strava, a team at the core of Strava's AI strategy, responsible for building the shared tooling that enables product teams to ship high value GenAI-powered features at scale
- This role sits at the intersection of AI engineering, platform engineering, and server engineering
- You will own the systems that make it easy and reliable for all of our product teams to build user facing features on top LLMs at Strava, from shared context, tool management, agent loops, orchestration, data access, search and retrieval to evaluation and ROI frameworks
- This is a high-leverage technical role: you're not just building infrastructure, you're building the core understanding of athletes that enable consistent athlete experiences, insight across product surfaces
- You'll work closely with product engineers, product managers and data teams to translate cutting-edge AI capabilities into production-ready platforms that facilitate development of AI features that provide value to our athletes
- We follow a flexible hybrid model that translates to more than half your time on-site in our San Francisco office — three days per week
- Build for a Well Loved Consumer Product: Work at the intersection of AI and fitness to launch and optimize product experiences that will be used by tens of millions of active people worldwide
- Build the GenAI + Discovery Platform: Set the vision, Design and the shared genAI platform: LLM, and workflow orchestration, prompt management systems, RAG pipelines, search and retrieval services (vector, hybrid and structured search), and evaluation tooling
- Enable Teams to Ship AI Features Faster: Build self-serve interfaces and golden paths so that product and CUJ engineering teams can build GenAI-powered features without deep AI expertise
- Own End-to-End AI Capability Delivery: Drive projects from architecture and interface design through production deployment and monitoring, ensuring correctness, latency, reliability, and cost-efficiency of the AI capabilities your platform serves
- Collaborate Across Engineering, and Product: Work closely with engineers and PMs across different verticals to enable the new features and build the genAI roadmap. inform product teams on how to consume and leverage AI capabilities effectively
- Build from a Rich Dataset: Explore and use Strava's extensive unique fitness and geo datasets from millions of users to inform how AI capabilities can extract actionable insights, improve product decisions, and power novel athlete experiences
- You Will Be Successful Here By:
- Treating AI Platform as a Product: Bringing engineering rigor — versioning, contracts, SLAs, monitoring, and deprecation paths — to AI capabilities and LLM integrations that product teams depend on. You don't ship a prototype; you ship a platform
- Leading as an Owner: Taking end-to-end accountability for the reliability and impact of the systems you build, including their correctness in production, their adoption by downstream teams, and the business outcomes they enable
- Building for Leverage: Designing platforms and tooling that multiply the output of the broader team, reducing the AI infrastructure expertise required for CUJ teams to ship GenAI-powered features
- Collaborating Across Disciplines: Working fluidly with ML engineers, data engineers, data scientists, and product managers to align on model selection, evaluation standards, prompt strategies, and consumption patterns
- Raising the Standard: Helping establish best practices for GenAI system development, responsible AI patterns, and operational health, and mentoring teammates at all levels to do the same
- Being passionate about the work you are doing and contributing positively to Strava's inclusive and collaborative team culture and values
Our take
Strava has created an online network where runners, swimmers and cyclists can record fitness activities, and compare and compete with their community. It offers both a free and premium subscription service with added features. The company also partners with local councils and urban planners who purchase valuable journey data from Strava which can be used to map out cities and develop safer cycle paths.
The platform helps members discover and plan workouts, as well as offering a leaderboard which is updated using GPS as users compete for the top spot on particular fitness segments.
With over 125 million athletes and growing, Strava released several new product rollouts in 2024, including an AI-enabled leaderboard. A partnership with the wearable fitness tracker Oura will mean Strava software is available on wearables, taking the company into fresh competition with the likes of Peloton and Apple. In 2025, the company secured new funding in a round led by Sequoia Capital, growing its value to $2.2 billion.
Freddie
Company Specialist at Welcome to the Jungle
Insights
-6% employee growth in 12 months
Company
Funding (last 2 of 5 rounds)
Nov 2020
$110m
SERIES F
Oct 2014
$18m
LATE VC
Total funding: $151.4m
Company benefits
- Competitive base salary & stock options
- 100% company paid benefits for employees and families
- Flexible paid time off
- $2,000 annual professional development stipend
- Paid time off for volunteering
- 401(k) plan - with company matching
- $1000 annual gear stipend
- $500 annual gym or coaching reimbursement
- On-site fitness rooms with showers, lockers, and towel service
- Weekly team workouts – including remote employees
- Safe and secure bike storage on-site
- Weekly all hands meetings
- Employee resource groups
- Anti-racism nonprofit company matching program
- Free lunch on Wednesdays on-site
- Regular team happy hours
- Team offsites and company retreats
- Cell phone reimbursement
- Generous industry discounts on gear and activities
- Race entries to events we sponsor
- Snacks and stocked kitchens on-site
- Strava gear
Company HQ
Mission District, San Francisco, CA
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