Senior Full Stack Engineer, AI Platform & Agents
Role details
Job location
Tech stack
Job description
In Health, we're launching UpToDate Expert AI - a medical research and clinical reasoning agent that transforms the world's most widely used point-of-care knowledge resource into a real-time medical assistant. Millions of physicians will rely on it to accelerate differential diagnosis, refine treatment decisions, and reduce cognitive load-while maintaining rigorous safety, privacy, and guideline fidelity. Improvements you ship (latency, reliability, hallucination reduction) will translate directly into faster, higher-quality patient care at global scale., * Design and implement full-stack applications, AI agents, and platform components that enable rapid GenAI agent development, validation, and deployment.
- Build developer tooling, CI/CD, and observability for safe, fast iteration (evals, canaries, rollout/rollback, cost and quality telemetry).
- Apply secure SDLC and privacy-by-design practices (threat modeling, least privilege).
- Collaborate with product, UX, and domain experts to deliver customer-focused solutions with measurable outcomes.
- Apply current LLM patterns (RAG, retrieval, routing, tool-use, evals) to deliver measurable customer value-faster, more reliable AI systems; reduced time-to-decision; improved trust/safety metrics; and lower cost per query.
- Lead by example through writing high-quality, maintainable code that demonstrates engineering craftsmanship., We value a "manager of one" mindset, where outcomes matter more than optics. Authority is earned through demonstrated impact, not tenure or title. You'll report directly to the VP of Engineering, AI Platform.
Requirements
You don't need to know all of these on day one, but you should be ready to learn quickly.
- TypeScript, Node.js, React, Python, LangChain/LangGraph, MCP/A2A, Rust
- AWS (primary), Azure, GCP; Docker, Terraform, GitHub Actions
- DocumentDB, DynamoDB, OpenSearch, Azure AI Search
- Azure OpenAI, AWS Anthropic, Google Gemini
- GitHub, Confluence, Slack, * 5+ years of professional software engineering experience.
- Strong full-stack development skills and cloud experience (AWS/Azure/GCP).
- Expert in at least one, and proficient across the others: AI Agent development and evaluation; backend development; frontend development; cloud services (AWS/Azure/GCP); CI/CD and Infrastructure as Code; Site Reliability Engineering (SRE); Quality engineering / testing strategy; Secure SDLC and privacy by design; Proven track record delivering secure, reliable, cloud-native systems to production; Excellent problem-solving, ownership, and cross-functional communication., * Proven ability to deliver software products independently or as part of a small, fast-paced team.
- Experience of taking AI agents from concept to production, including safety evaluations, iterative testing (e.g., A/B testing), and continuous improvement.
- Experience with LangChain/LangGraph and MCP; vector/RAG systems; OpenSearch.
- Worked on traditional ML tasks like training, deployment, and monitoring.
- Understand how LLMs work, their failure modes, and techniques like fine-tuning and model adaptation.
- Familiarity with regulatory frameworks such as SOC2, HIPAA, etc.