Senior Agentic AI Platform Engineer

CVS Health

. Design, develop, and maintain reusable platform components, accelerators, pipelines, agent harnesses, and shared services across Google Vertex AI, ServiceNow AI, Databricks, and Claude-based ecosystems .

Posted 10/28/2026full-timeRemote • Connecticut • United StatesSenior💰 $101,970 - $203,940 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining AI/ML platforms and reusable engineering frameworks, with a strong focus on secure, scalable, and high-performance solutions. Proficient in collaborating with cross-functional teams to drive adoption and provide technical guidance while mentoring junior resources.

Highest-signal resume keywords

AI/ML Platform DevelopmentGoogle Vertex AIPython EngineeringRAG Architecture DesignSecure System Implementation

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Hard Skills

AI GovernanceProduction SolutionsMicroservice ArchitectureFastAPIDockerCI/CDVector Search SolutionsPrompt EngineeringSQLETL Pipelines

Soft Skills

Technical LeadershipMentoringCommunication

Tools & Technologies

ServiceNow AIDatabricksClaudePgvectorCloud SQLCloud Functions

Industry Keywords

HealthcarePharmacyCybersecurityAIOpsMLOps

Tech Stack

Tools & technologies

AzureCloudCyber SecurityDistributed SystemsDockerETLPythonServiceNowSQL

About the role

Key responsibilities & impact

Design, develop, and maintain reusable platform components, accelerators, pipelines, agent harnesses, and shared services across Google Vertex AI, ServiceNow AI, Databricks, and Claude-based ecosystems
Build foundational enterprise AI capabilities including RAG frameworks, vector-enabled architectures, evaluation frameworks, orchestration services, model integration patterns, and reusable engineering accelerators
Own shared platform capabilities through architecture, versioning, production hardening, performance optimization, adoption support, and continuous enhancement
Implement secure-by-design patterns with AI governance, access controls, data privacy protections, prompt injection safeguards, resiliency mechanisms, failover strategies, and graceful degradation
Partner with AI Solutions Architects, Product Delivery, Architecture, Security, and Operations teams to drive adoption and provide onboarding and technical guidance
Communicate architectural decisions and technical trade-offs to engineering teams and senior leadership
Mentor interns and contractor resources and provide technical leadership and engineering best-practice guidance

Requirements

What you’ll need

5+ years building AI/ML platforms, developer platforms, shared engineering frameworks, or enterprise-scale software solutions with increasing technical ownership and responsibility
4+ years developing reusable platform capabilities, accelerators, tooling, or shared services adopted across multiple engineering teams in enterprise environments
3+ years of hands-on experience building production solutions on Google Vertex AI, Azure AI, ServiceNow AI, Databricks, or similar cloud AI platforms
2+ years designing and implementing RAG, agentic AI architectures, vector search solutions, and large language model integrations
2+ years designing secure, scalable, highly available distributed systems while applying AI governance, privacy, resiliency, and operational reliability best practices
Strong full-stack and Python engineering expertise, including production-grade development, API and microservice architecture, FastAPI, Docker, pytest, CI/CD, and cloud-native application design
Experience building agentic AI solutions using Claude or similar large language models, tool use, function calling, agent orchestration, MCP, and multi-step reasoning patterns
Knowledge of prompt engineering, context engineering, retrieval engineering, chunking strategies, embedding models, vector databases such as pgvector, retrieval tuning, reranking, caching strategies, and evaluation frameworks
Familiarity with document ingestion and parsing frameworks such as Docling or Unstructured; SQL, schema migration tooling, ETL pipelines, and bronze, silver, and gold data architectures
Experience supporting healthcare, pharmacy, cybersecurity, AIOps, or other regulated environments; exposure to MLOps, LLMOps, Cloud SQL, Cloud Functions, and IAM
Bachelor’s degree from accredited university or equivalent work experience (HS diploma + 4 years relevant experience)

Benefits

Comp & perks

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