Principal Engineer, Clinical Data and AI Platforms

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary We're building the platform that turns clinical, claims and document data into insight for patients, providers and payers. As Principal Engineer, you'll design and build that platform on Google Cloud, and lead how our teams use AI agents to develop and operate it. The scope is broad and the pace is fast: priorities and requirements evolve quickly, and the systems we build will evolve with them. You'll bring creative problem solving, a collaborative approach and an AI-first way of working. You'll also bring the discipline to run well-governed systems in a regulated environment. Primary Responsibilities Platform design • Design the platform architecture on Google Cloud with engineering leadership. It spans data acquisition, identity resolution, FHIR harmonization, data products, LLM and rules engines, as well as customer-facing products. • Design systems to evolve quickly as needs change, and lead their evolution over time. • Frame key trade-offs in isolation, data rights, scale, reliability and cost, and recommend options. Engineering • Write production code for the platform's most critical and complex components. • Turn prototypes into reference implementations that teams can adopt. AI-assisted development • Lead the development of practices for using AI coding agents, including specifications, guardrails, code review, evaluation and human oversight. • Run pilots with engineering teams, measure the effect on delivery speed and quality, and recommend practices for wider adoption. • Maintain architecture, diagrams and documentation as code, so engineers and AI agents work from the same source. AI-assisted operations • Design AI-assisted operations for incident triage, runbook automation, and capacity and cost management. • Build in approval gates, least-privilege access for AI agents, and a full audit trail of agent actions. • Propose service-level objectives and the observability needed to measure the impact of automation. Compliance and controls • Design for enterprise control conformance within the systems we build, including change management, separation of duties, access reviews, data lineage, and model and prompt governance. • Automate the collection of audit evidence, in partnership with security, privacy, compliance and AI governance teams. Communication • Explain complex systems clearly to engineers, product leaders, executives and customers, in writing and in diagrams. • Help develop technical business cases and present them to senior leadership. Required Qualifications • 12+ years of experience building production distributed systems. • 5+ years leading architecture across multiple teams at the staff or principal level. • Experience designing and delivering large-scale batch and streaming data platforms in a demanding engineering environment. • Current, hands-on coding experience in Python and either Go, Java, or C#. • Deep experience with cloud platforms, preferably Google Cloud, including GKE, BigQuery, Spanner, Dataflow, Pub/Sub, Vertex AI and VPC Service Controls. • Production experience with machine learning or large language model systems, including retrieval, extraction, evaluation and serving at scale. • Extensive use of AI agents across your own design, development, testing and code review work, with measurable impact on delivery.