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Strava

Fitness tracking and social network platform

Staff AI Engineer

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA$260k - $280k /yr

About the Job

Requirements

  • At least 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 large language model or machine learning systems, with a strong instinct for application programming interface design, versioning, and self-service patterns.
  • Hands-on experience building with large language models in production, including agentic workflows, prompt and context engineering, retrieval-augmented generation architectures, embedding pipelines, fine-tuning workflows, or large language model evaluation frameworks and tools such as LangChain.
  • Proficiency in search systems such as Elasticsearch, OpenSearch, and vector search.
  • Proficiency in backend service development on cloud environments, preferably Amazon Web Services, using Python or Go.
  • A solid understanding of distributed systems and containerized infrastructure, including Kubernetes and Docker.
  • Ability to lead multi-team projects, define technical direction, and grow engineers at multiple levels.
  • Strong judgment in applying evolving generative AI capabilities, model capabilities, agent frameworks, and multimodal systems to real product problems.
  • Ability to align cross-functional partners around technical direction and build organizational trust in the platforms the team ships.

Responsibilities

  • Set the vision and design the shared generative AI platform, including large language models and workflow orchestration, prompt management systems, retrieval-augmented generation pipelines, search and retrieval services, and evaluation tooling.
  • Build self-service interfaces and golden paths that enable product and customer-user-journey engineering teams to build generative-AI-powered features without deep AI expertise.
  • Drive projects from architecture and interface design through production deployment and monitoring, ensuring correctness, latency, reliability, and cost-efficiency of the AI capabilities the platform serves.
  • Work closely with engineers and product managers across verticals to enable new features and build the generative AI roadmap; inform product teams how to consume and leverage AI capabilities effectively.
  • Explore and use Strava's fitness and geospatial datasets to inform how AI capabilities extract actionable insights, improve product decisions, and power athlete experiences.
  • Apply engineering rigor to AI capabilities and large language model integrations through versioning, contracts, service-level agreements, monitoring, and deprecation paths.
  • Take end-to-end accountability for the reliability and impact of systems built, including production correctness, downstream team adoption, and business outcomes.
  • Design platforms and tooling that multiply the broader team's output and reduce the AI infrastructure expertise required for customer-user-journey teams to ship generative-AI-powered features.
  • Collaborate with machine learning engineers, data engineers, data scientists, and product managers to align on model selection, evaluation standards, prompt strategies, and consumption patterns.
  • Establish best practices for generative AI system development, responsible AI patterns, and operational health, and mentor teammates at all levels.
  • Launch and optimize consumer product experiences at the intersection of AI and fitness.

Desired Qualifications

  • Experience building AI platform tooling or developer-facing infrastructure, ideally for large language model or machine learning systems.
  • Experience with Amazon Web Services is preferred.

About the Company

Strava

Fitness tracking and social network platform

Strava records, tracks, and analyzes athletic activities, offering metrics like speed, pace, and distance, plus features such as performance comparison and Relative Effort. It operates on a freemium model, with basic functions free and Premium subscriptions unlocking advanced training plans, route planning, and deeper analytics. It also serves as a social network for athletes, allowing users to share activities, connect with others, and discover routes, races, and clubs across GPS-compatible devices and iPhone, Android, and web apps. The goal is to help athletes train more effectively, stay motivated, and improve performance while monetizing through premium memberships.

Company size
1,001-5,000
Company stage
Series F
Total funding
$151.4M
Headquarters
San Francisco, CA
Founded
2009

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