Principal AI Engineer

CVS Health

. Set the technical direction for enterprise-grade GenAI and agentic AI systems in a regulated healthcare environment .

Posted 10/27/2026full-timeRemote • United StatesLead💰 $144,200 - $288,400 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in architecting and delivering enterprise-grade GenAI and agentic AI solutions within regulated healthcare environments, emphasizing secure AI practices and compliance with privacy and audit requirements. Proven ability to lead technical direction and collaborate across teams to translate strategic needs into scalable AI systems.

Highest-signal resume keywords

GenAI ArchitectureAWS and/or GCP ExperienceMicroservices and API DevelopmentAI/ML Systems in Regulated EnvironmentsTechnical Leadership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Node.jsTypeScriptJavaPythonInfrastructure-as-CodeCI/CDServerless ArchitecturesEvent-Driven ArchitecturesVector DatabasesRAG Architectures

Soft Skills

MentorshipCollaborationInfluencing Without Authority

Tools & Technologies

AWS BedrockGCP Vertex AIKubernetesMCP ServersObservability Platforms

Certifications & Qualifications

Cloud Certifications

Industry Keywords

HealthcareHIPAAPHI HandlingAI Governance FrameworksModel Risk Management

Tech Stack

Tools & technologies

AWSCloudGoogle Cloud PlatformJavaJavaScriptKubernetesMicroservicesNode.jsPythonTypeScript

About the role

Key responsibilities & impact

Set the technical direction for enterprise-grade GenAI and agentic AI systems in a regulated healthcare environment
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 addressing privacy, security, governance, auditability, model risk, and human oversight
Define AI architecture, standards, and engineering best practices for agent orchestration, RAG, tool/MCP integrations, evaluation, and enterprise AI adoption
Partner with product, engineering, data, security, privacy, legal, compliance, and business teams to translate strategic needs into scalable AI solutions
Provide hands-on technical leadership through design reviews, mentorship, architecture guidance, build-vs-buy decisions, and technical documentation
Report to the Lead Director on the Commercial team in the Aetna Technology organization

Requirements

What you’ll need

10+ years of software engineering experience, with 5+ years in solution architecture or system design
5+ years building large-scale microservices and APIs using Node.js, TypeScript, Java, or Python
5+ years of hands-on AWS and/or GCP experience, including serverless, event-driven, CI/CD, and AI/ML
Hands-on experience with AWS Bedrock or GCP Vertex AI, or equivalent
Production experience with agentic AI frameworks, RAG architectures, and vector databases
Strong Python skills for AI/ML engineering
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
Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience (High School diploma + 4 years of relevant experience)
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
Experience with MCP servers and tool integration, agent-to-agent patterns, and agent memory design
Experience with infrastructure-as-code, containers, and Kubernetes
Experience with fine-tuning techniques and open-weight models
Familiarity with AI governance frameworks and model risk management
Agile/SAFe experience in large enterprises
Cloud certifications
Publications, patents, or open-source contributions in AI/ML

Benefits

Comp & perks

Medical coverage
Dental coverage
Vision coverage
Paid time off
Retirement savings options
Wellness programs
Other resources supporting physical, emotional, and financial well-being
CVS Health bonus, commission or short-term incentive program
Equity award program