Sr. Full-Stack Engineer, Applied AI

Hims & Hers is the leading health and wellness platform, on a mission to help the world feel great through the power of better health. They are seeking a Sr. Full-Stack Engineer to join the Applied AI team to build the core infrastructure that powers their next generation of AI-powered health experiences.

Responsibilities:

• Design and build scalable AI workflow systems — including orchestration runtimes, SDKs, and observability pipelines that power real-time, intelligent experiences
• Develop end-to-end features using TypeScript (Cloudflare Workers, React/Next.js) and Python (Databricks, evaluation, data processing)
• Integrate and evaluate large language models (LLMs) and other ML systems (OpenAI, Anthropic, Vertex, Databricks) via a unified AI Gateway
• Build tool connectors and APIs for our internal domains — EHR, Pharmacy, Payments, Orders, Care — enabling safe and automated cross-system workflows
• Develop evaluation and feedback systems that measure quality, grounding, latency, and safety of AI-powered flows
• Partner closely with AI, Product, and Infra teams to design, prototype, and iterate quickly — turning research into production capabilities
• Contribute to shared TypeScript and Python SDKs that standardize event schemas, tool contracts, and developer experience across Applied AI
• Ensure everything you build meets security-by-design and privacy-first principles, supporting HIPAA and compliance requirements
• Foster a build → measure → learn culture by testing fast, gathering feedback, and continuously improving the system

Requirements:

• 4+ years of professional full-stack experience, spanning backend APIs, frontend apps, infra, and data systems
• Proficient in TypeScript (Node.js, React) and Python (data pipelines, ML evaluation, orchestration)
• Familiarity with LLM- or ML-based systems, including prompt orchestration, evaluation harnesses, or RAG pipelines
• Experience with workflow orchestration tools
• Understanding of system design for AI workloads — including state management, retries, idempotency, and performance optimization
• Experience with data/ML infrastructure (Databricks, AWS, vector stores, or BigQuery)
• A bias toward action and iteration — you build fast, validate ideas early, and improve based on results
• Collaborative mindset, with strong communication skills
• Awareness of AI lifecycle management — from experimentation and evaluation to safety and deployment
• Building AI evaluation or observability systems, such as LLM-as-a-judge frameworks or human review pipelines
• Experience with Databricks, Cloudflare Durable Objects, or other edge orchestration systems
• Background in healthcare, life sciences, or regulated industries
• Contributions to open-source SDKs or AI infrastructure projects
• Experience creating visual workflow editors or n8n-style automation tools