• Lead architecture and platform development • Design and own core AI workflow platforms, orchestration systems, and shared SDKs that power intelligent healthcare experiences. • Build scalable, reliable systems for LLM orchestration, grounding, evaluation, and agent-like workflows. • Create reusable frameworks and patterns that other engineering teams can adopt across the company. • Drive multi-quarter technical initiatives and help bridge AI research prototypes with production-grade systems. • Partner closely with Product across multiple verticals • Work with Pharmacy, E-commerce, Care, and Operations to bring AI-powered features to life, from patient-facing journeys to internal efficiency tools. • Collaborate on product strategy, helping translate ambiguous ideas into clear technical plans. • Support teams in releasing features quickly through incremental, high-velocity delivery cycles. • Ensure user-facing AI experiences meet expectations for performance, reliability and usability. • Champion safety, privacy, and clinical integrity • Develop evaluation frameworks and observability systems that measure AI behavior, grounding, safety, and quality. • Establish guardrails and patterns that ensure all AI interactions comply with HIPAA, security-by-design, and privacy-first principles. • Work with clinical, legal, and AI safety partners to ensure our systems are trustworthy and appropriate for healthcare use. • Elevate engineering excellence • Mentor engineers and help cultivate strong engineering practices across the Applied AI organization. • Lead design reviews and contribute to architectural governance across engineering teams. • Improve developer experience and remove platform bottlenecks that slow down product teams. • Raise the overall quality bar by championing clear standards for reliability, observability, testing, and iteration. • Build and ship across the full stack • Develop features and infrastructure using TypeScript (AWS, Cloudflare Workers, React/Next.js) and Python (Databricks, orchestration, evaluation). • Integrate and evaluate LLMs and ML systems through unified AI gateway. • Build secure APIs and connectors that link to domains like EHR, Pharmacy, Payments, Orders, and Care. • Contribute to shared libraries that standardize schemas, tool contracts, and developer experience.