Senior Agentic AI Platform Engineer

CVS Health • Work At Home-Connecticut, CT

3d • $101,970 - $203,940

About The Position

CVS Health is hiring a Senior Agentic AI Platform Engineer for its AI/ML Solutions Delivery organization. The role builds foundational platform capabilities that accelerate enterprise adoption of agentic AI solutions. As a full-stack platform engineer, this position designs, develops, and operationalizes reusable components, accelerators, pipelines, frameworks, and agent harnesses to help product delivery teams move from prototype to production. Technologies mentioned include Google Vertex AI, ServiceNow AI, Databricks, Claude, Python, APIs, and cloud-native services.

The engineer owns the end-to-end lifecycle of shared platform assets, creating secure, scalable, resilient, and high-performing capabilities for use across AI applications. The role partners with AI Solutions Architects and Product Delivery teams to align platform investments with business needs, engineering standards, and enterprise governance. It also provides technical leadership, coaching, and engineering best-practice guidance to contractor resources and interns.

Requirements

• At least 5 years building AI/ML platforms, developer platforms, shared engineering frameworks, or enterprise-scale software solutions, with increasing technical ownership and responsibility.
• At least 4 years developing reusable platform capabilities, accelerators, tooling, or shared services adopted across multiple engineering teams in enterprise environments.
• At least 3 years of hands-on experience building production solutions on Google Vertex AI, Azure AI, ServiceNow AI, Databricks, or similar cloud AI platforms.
• At least 2 years designing and implementing retrieval-augmented generation (RAG), agentic AI architectures, vector search solutions, and large language model integrations.
• At least 2 years designing secure, scalable, highly available distributed systems and applying AI governance, privacy, resiliency, and operational reliability best practices in fast-paced delivery environments.
• Bachelor’s degree from an accredited university or equivalent work experience; the posting specifies a high school diploma plus 4 years of relevant experience as an alternative.

Nice To Haves

• Strong full-stack and Python engineering expertise, including production-grade development, API and microservice architecture, FastAPI, Docker, pytest, CI/CD practices, and cloud-native application design.
• Experience building agentic AI solutions using Claude or similar large language models, including tool use, function calling, agent orchestration, Model Context Protocol (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; data engineering practices including 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.
• Ability to apply pragmatic technical judgment when selecting between AI-powered and traditional automation approaches.

Responsibilities

• 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 enterprise AI development capabilities, including RAG frameworks, vector-enabled architectures, evaluation frameworks, orchestration services, model integration patterns, and reusable engineering accelerators.
• Own platform capabilities throughout their lifecycle, including architecture, versioning strategy, production hardening, performance optimization, adoption support, and continuous enhancement; make and defend key technical trade-offs.
• Implement secure-by-design platform patterns incorporating AI governance, access controls, data privacy protections, prompt injection safeguards, resiliency mechanisms, failover strategies, and graceful degradation.
• Partner with AI Solutions Architects, Product Delivery teams, Architecture, Security, and Operations organizations to drive platform adoption and provide onboarding and technical guidance.
• Communicate architectural decisions and trade-offs to engineering teams and senior leadership.
• Mentor interns and contractor resources and provide technical leadership and engineering best-practice guidance.

Benefits

• Medical coverage
• Dental coverage
• Vision coverage
• Paid time off
• Retirement savings options
• Wellness programs
• Other resources, based on eligibility
• Eligible for a CVS Health bonus, commission, or short-term incentive program in addition to base pay

What This Job Offers

• Job Type: Full-time
• Career Level: Senior