Principal Engineer, Clinical Data and AI Platforms

CVS Health•Washington, DC

5d•$144,200 - $288,400

About The Position

CVS Health is seeking a Principal Engineer to design and build a Google Cloud platform that turns clinical, claims and document data into insights for patients, providers and payers. The role leads platform architecture and engineering, as well as the development of practices for using AI agents to develop and operate systems. The work spans data acquisition, identity resolution, FHIR harmonization, data products, LLM and rules engines, and customer-facing products. Requirements and priorities may evolve quickly, and the platform must be adaptable while meeting governance needs in a regulated environment. The Principal Engineer will write production code for critical components, establish reference implementations, and guide AI-assisted development and operations. This includes piloting AI coding-agent practices, measuring their effects on delivery speed and quality, designing approval and access controls for operational agents, and maintaining architecture and documentation as code. The role also designs enterprise controls, automates audit evidence collection with partner teams, communicates complex systems to technical and business audiences, and helps develop and present technical business cases. The role requires 12 or more years building production distributed systems and at least five years leading architecture across multiple teams at staff or principal level. Candidates should have hands-on coding experience in Python and Go, Java or C#, experience with large-scale batch and streaming platforms, cloud systems, production ML or LLM systems, extensive use of AI agents, and experience designing controls in regulated environments. A bachelor’s degree in a related technical field or equivalent experience is required; a master’s degree is preferred. The stated pay range is $144,200 to $288,400. The position is eligible for a CVS Health bonus, commission or short-term incentive program and an equity award target. This full-time role offers a comprehensive benefits package, including medical, dental and vision coverage, paid time off, retirement savings options and wellness programs, subject to eligibility.

Requirements

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 personal design, development, testing and code review work, with measurable impact on delivery.
Creative and collaborative problem-solving approach, and comfort with ambiguity and changing requirements.
Experience in a regulated environment, including designing controls and supporting systems through audits.
Strong written communication and diagramming skills, and experience presenting to senior executives.
Bachelor’s degree in computer science, engineering or a related technical field, or equivalent experience.

Nice To Haves

Master’s degree.
Experience with healthcare data standards, including FHIR, HL7v2, C-CDA, X12 claims, OMOP and CQL, and national health information exchange through TEFCA and QHINs.
Experience with master patient index and identity resolution at population scale.
Payer or provider domain experience, such as quality measurement, risk adjustment, utilization management or care management.
Security architecture experience, including zero trust, attribute- and relationship-based access control, and threat modeling.
Experience leading teams’ adoption of AI-assisted development practices.
Public technical work, such as open-source contributions, conference talks or published writing.

Responsibilities

Design the Google Cloud platform architecture with engineering leadership across data acquisition, identity resolution, FHIR harmonization, data products, LLM and rules engines, and customer-facing products.
Design systems that can evolve as needs change and lead their evolution over time.
Evaluate and recommend trade-offs involving isolation, data rights, scale, reliability and cost.
Write production code for the platform’s most critical and complex components.
Turn prototypes into reference implementations that teams can adopt.
Lead practices for AI coding agents, including specifications, guardrails, code review, evaluation and human oversight.
Run pilots with engineering teams, measure effects on delivery speed and quality, and recommend practices for wider adoption.
Maintain architecture, diagrams and documentation as code so engineers and AI agents use a shared source.
Design AI-assisted operations for incident triage, runbook automation, and capacity and cost management.
Build 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 automation impact.
Design systems for enterprise control conformance, including change management, separation of duties, access reviews, data lineage, and model and prompt governance.
Automate audit evidence collection in partnership with security, privacy, compliance and AI governance teams.
Explain complex systems clearly to engineers, product leaders, executives and customers in writing and diagrams.
Help develop technical business cases and present them to senior leadership.