Staff Software Engineer, AI Operations

We are building a new, high-velocity squad within our Health Intelligence organization. This team is tasked with moving from data and insights to action and orchestration. We are looking for engineers who don't just use AI as a feature, but who use AI as a fundamental building block of both the product they build and the way they write code.

This is a fast-moving, LLM-forward team. We prioritize rapid prototyping, iterative loops, and AI-native development. You will be part of a US-based pillar designed to operate with the speed of a startup while leveraging the deep data moats of a global health leader.

As a Staff Engineer on this team, you will architect the backend systems and web interfaces that bridge the gap between complex health data and real-world user utility. You will be responsible for building the connective tissue that allows AI models to interact with external APIs, communication protocols, and personalized data layers.

This is a hybrid/in office role reporting to our San Francisco location.

• →Rapid Prototyping: Move from concept to production in days, not months. You’ll build and validate new interaction layers that bring health intelligence to users where they already are.
• →AI Orchestration: Design and implement backend logic for LLM-based agents, focusing on reliability, context-window management, and tool-calling (agentic workflows).
• →Full-Stack Ownership: While backend-heavy, you are comfortable spinning up modern web frontends or jumping into native iOS or Android development to test user experiences and gather immediate feedback. You use the tools available to deploy solutions across platforms and aren’t limited to a single stack.
• →AI-Native Development: You will be expected to lead the way in AI-augmented engineering—utilizing tools like Claude Code, Cursor, and automated refactoring to maintain a velocity that traditional teams can't match.
• →Systems Integration: Build secure, scalable integrations between our internal intelligence engine and third-party service providers.
• →Applied MLOps: You understand that "AI in production" is more than just an API call. You have experience with MLOps best practices, including model monitoring, evaluation frameworks (LLM-as-a-judge), versioning, and deploying scalable data pipelines that fuel RAG systems.

• An experienced builder: You have 5+ years building and maintaining production systems
• Product-Minded Engineer: You care more about the user win than the specific technology stack. You have a builder mindset and a bias toward action.
• LLM Power User: You have experience building with OpenAI, Anthropic, or LangChain/LlamaIndex, and you understand the nuances of prompt engineering and RAG (Retrieval-Augmented Generation).
• Technically Versatile: You are an expert in at least one backend language (Python, or Node.js) and have a strong grasp of modern frontend frameworks (React/Next.js) or native development (Swift/Kotlin).
• Security & Privacy Conscious: You understand the responsibility of handling sensitive personal data and design systems with privacy by design as a default.
• High Agency: You thrive in ambiguity. You don't wait for a 50-page PRD; you help define the requirements through experimentation.

• Experience in the Digital Health or MedTech space.
• A history of building conversational interfaces or automated concierge services.
• Contributions to open-source AI projects or a portfolio of weekend projects leveraging the latest LLM capabilities.