Job description

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 As a Principal AI Engineer, you will set the technical direction for how we design, build, and operate enterprise-grade GenAI and agentic AI systems in a regulated healthcare environment. You will be a hands-on technical leader who works across data science, clinical, product, security, privacy, legal, and business teams to turn strategic priorities into trustworthy, scalable, production AI solutions. You will report to the Lead Director on the Commercial team in our Aetna Technology organization. What You Will Do Architect and deliver production-grade GenAI and agentic AI solutions, including RAG, vector search, model integration, tool orchestration, guardrails, and evaluation across AWS and/or GCP. Build scalable, cloud-native AI systems using serverless/event-driven architectures, APIs, CI/CD, infrastructure-as-code, and modern software engineering practices. Own the production AI lifecycle, from experimentation and deployment through monitoring, observability, performance, cost optimization, and continuous improvement. Establish secure and responsible AI practices that address privacy, security, governance, auditability, model risk, and appropriate human oversight in a regulated environment. Define AI architecture, standards, and engineering best practices for areas such as agent orchestration, RAG, tool/MCP integrations, evaluation, and enterprise AI adoption. Partner across product, engineering, data, security, privacy, legal, compliance, and business teams to translate strategic needs into scalable AI solutions and influence technical direction. Provide hands-on technical leadership through design reviews, mentorship, architecture guidance, build-vs-buy decisions, and clear technical documentation. Required Qualifications 10 years of software engineering experience, with 5 years in solution architecture or system design. 5 years building large-scale microservices and APIs (Node.js, TypeScript, Java, or Python). 5 years of hands-on AWS and/or GCP experience (serverless, event-driven, CI/CD, AI/ML). Hands-on experience with AWS Bedrock (models, agents, knowledge bases, guardrails, tuning, evaluation) or GCP Vertex AI (Model Garden, Agent Builder, Vector Search, Pipelines, Tuning), or equivalent. Production experience with agentic AI frameworks, RAG architectures, and vector databases. Strong Python skills for AI/ML engineering. Demonstrated experience delivering AI/ML systems in regulated environments with security, privacy, and audit requirements. Track record of influencing technical direction across multiple teams without direct authority. Preferred Qualifications Healthcare, life sciences, or other regulated-industry experience, including HIPAA and PHI handling. Experience with Vertex AI Generative AI Studio, vector search orchestration, and agent capabilities. Experience with LLM evaluation tooling and observability platforms (e.g., LangSmith, Arize, Langfuse, Ragas, or cloud-native equivalents). Experience with MCP servers and tool integration, agent-to-agent patterns, and agent memory design. Experience with infrastructure-as-code (Terraform, CDK), containers, and Kubernetes. Experience with fine-tuning techniques (LoRA/PEFT, distillation) and open-weight models. Familiarity with AI governance frameworks (NIST AI RMF, ISO 42001) and model risk management. Agile/SAFe experience in large enterprises. Cloud certifications (AWS, GCP, or Azure). Publications, patents, or open-source contributions in AI/ML. Education Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience (High School diploma 4 years of relevant experience). Pay Range The typical pay range for this role is: $144,200.00 - $288,400.00 This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above. This position also includes an award target in the company’s equity award program. Our people fuel our future. Our teams reflect the customers, patients, members and communities we serve and we are committed to fostering a workplace where every colleague feels valued and that they belong. Great benefits for great people We take pride in offering a comprehensive and competitive mix of pay and benefits that reflects our commitment to our colleagues and their families. This full‑time position is eligible for a comprehensive benefits package designed to support the physical, emotional, and financial well‑being of colleagues and their families. The benefits for this position include medical, dental, and vision coverage, paid time off, retirement savings options, wellness programs, and other resources, based on eligibility. Additional details about available benefits are provided during the application process and on Benefits Moments . We anticipate the application window for this opening will close on: 11/26/2026 Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.

Requirements

Must-haves

Architect and deliver production-grade GenAI and agentic AI solutions, including RAG, vector search, model integration, tool orchestration, guardrails, and evaluation across AWS and/or GCP.
Build scalable, cloud-native AI systems using serverless/event-driven architectures, APIs, CI/CD, infrastructure-as-code, and modern software engineering practices.
Own the production AI lifecycle, from experimentation and deployment through monitoring, observability, performance, cost optimization, and continuous improvement.
Establish secure and responsible AI practices that address privacy, security, governance, auditability, model risk, and appropriate human oversight in a regulated environment.
Define AI architecture, standards, and engineering best practices for areas such as agent orchestration, RAG, tool/MCP integrations, evaluation, and enterprise AI adoption.
Partner across product, engineering, data, security, privacy, legal, compliance, and business teams to translate strategic needs into scalable AI solutions and influence technical direction.
Provide hands-on technical leadership through design reviews, mentorship, architecture guidance, build-vs-buy decisions, and clear technical documentation.
10 years of software engineering experience, with 5 years in solution architecture or system design.
5 years building large-scale microservices and APIs (Node.js, TypeScript, Java, or Python).
5 years of hands-on AWS and/or GCP experience (serverless, event-driven, CI/CD, AI/ML).
Hands-on experience with AWS Bedrock (models, agents, knowledge bases, guardrails, tuning, evaluation) or GCP Vertex AI (Model Garden, Agent Builder, Vector Search, Pipelines, Tuning), or equivalent.
Production experience with agentic AI frameworks, RAG architectures, and vector databases.

Nice-to-haves

Healthcare, life sciences, or other regulated-industry experience, including HIPAA and PHI handling.
Experience with Vertex AI Generative AI Studio, vector search orchestration, and agent capabilities.
Experience with LLM evaluation tooling and observability platforms (e.g., LangSmith, Arize, Langfuse, Ragas, or cloud-native equivalents).
Experience with MCP servers and tool integration, agent-to-agent patterns, and agent memory design.
Experience with infrastructure-as-code (Terraform, CDK), containers, and Kubernetes.
Experience with fine-tuning techniques (LoRA/PEFT, distillation) and open-weight models.
Familiarity with AI governance frameworks (NIST AI RMF, ISO 42001) and model risk management.
Agile/SAFe experience in large enterprises.
Cloud certifications (AWS, GCP, or Azure).
Publications, patents, or open-source contributions in AI/ML.
$144,200.00 - $288,400.00
Our people fuel our future. Our teams reflect the customers, patients, members and communities we serve and we are committed to fostering a workplace where every colleague feels valued and that they belong.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiawsgcpci/cdnode.jstypescriptjavapythonmlllmkubernetesagileazure

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Dental

Vision

Paid Time Off

Wellness