Lead Agentic AI Solutions Engineer

CVS Health

. Design, develop, and deploy production-grade agentic AI and intelligent automation solutions using ServiceNow, Databricks, Google Vertex AI, Azure AI Foundry, and Anthropic Claude .

Posted 11/10/2026full-timeRemote • Connecticut • United StatesSenior💰 $130,295 - $260,590 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying agentic AI and intelligent automation solutions, with a strong focus on cloud-native architectures, AI governance, and security practices. Proven ability to lead technical initiatives, mentor teams, and establish best practices in enterprise AI engineering.

Highest-signal resume keywords

Agentic AI Solution DevelopmentCloud-Native System DesignPython Application DevelopmentMulti-Agent System ArchitectureAI Governance and Security

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI/ML DevelopmentWorkflow OrchestrationRAG ArchitecturePrompt EngineeringContext EngineeringVector SearchDocument IngestionCI/CD AutomationMicroservices DevelopmentTesting Harness Implementation

Soft Skills

Technical MentorshipCollaborationLeadership

Tools & Technologies

ServiceNowDatabricksGoogle Vertex AIAzure AI FoundryAnthropic ClaudeFastAPIDockerPytestSQLETL Pipelines

Industry Keywords

CybersecurityHealthcareInsuranceAIOpsSecOpsRegulated Environments

Tech Stack

Tools & technologies

AzureCloudCyber SecurityDockerETLMicroservicesPythonServiceNowSQL

About the role

Key responsibilities & impact

Design, develop, and deploy production-grade agentic AI and intelligent automation solutions using ServiceNow, Databricks, Google Vertex AI, Azure AI Foundry, and Anthropic Claude
Deliver AI-powered capabilities for IT Operations and Cybersecurity, including incident triage, alert correlation, workflow orchestration, operational decision support, and intelligent remediation
Design and implement end-to-end agentic AI systems using multi-agent architectures, prompt engineering, context engineering, tool orchestration, memory frameworks, AI guardrails, and evaluation frameworks
Build and optimize RAG, GraphRAG, vector search, document ingestion, and enterprise knowledge integration solutions
Lead the full solution lifecycle from architecture and prototyping through production deployment, monitoring, optimization, and continuous improvement
Implement secure-by-design architectures with AI security controls, data privacy protections, prompt injection safeguards, resiliency patterns, failover mechanisms, and responsible AI practices
Collaborate with Architecture, Cybersecurity, Platform Engineering, Product, and Operations teams
Provide technical mentorship to interns and contractor resources
Serve as a technical lead for assigned initiatives and establish enterprise AI engineering standards and best practices
Own application architecture, backend services, AI orchestration, data integration, deployment, and operational support

Requirements

What you’ll need

7+ years developing software, AI/ML, intelligent automation, or full-stack applications with demonstrated ownership of complex enterprise solutions
5+ years designing scalable cloud-native systems while applying AI governance, security, privacy, access management, resiliency, and operational reliability best practices
Proven track record delivering production-ready automation, generative AI, or agentic AI solutions beyond proof-of-concept environments
Experience building multi-agent systems, workflow orchestration solutions, or intelligent automation platforms
3+ years building Python-based applications, APIs, microservices, and cloud-native services
Experience with modern software engineering practices, CI/CD pipelines, and automated testing approaches
Hands-on experience implementing RAG architectures, vector search, document ingestion, LLM integrations, prompt engineering, context engineering, evaluation frameworks, testing harnesses, and agent performance measurement methodologies within enterprise environments
Experience building agentic AI solutions utilizing Claude or similar large language models, including tool use, function calling, agent orchestration, multi-agent architectures, and multi-step reasoning
Knowledge of RAG and GraphRAG architectures, embedding models, vector databases such as pgvector, retrieval optimization, reranking techniques, semantic search frameworks, and memory architectures
Experience with agent engineering concepts including prompt engineering, context engineering, AI guardrails, evaluation frameworks, benchmark testing, model observability, and responsible AI controls
Familiarity with FastAPI, Docker, pytest, document-processing frameworks such as Docling or Unstructured, modern data engineering practices, SQL, ETL pipelines, MLOps, LLMOps, and CI/CD automation
Experience supporting healthcare, pharmacy, insurance, cybersecurity, AIOps, SecOps, or other highly regulated environments
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
Award target in the company’s equity award program
Medical coverage
Dental coverage
Vision coverage
Paid time off
Retirement savings options
Wellness programs
Other resources supporting physical, emotional, and financial well-being