Senior Manager AI Engineer

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.

• Build, lead, mentor, and develop a high-performing team of AI and software engineers while fostering a culture of innovation, accountability, and continuous learning.

• Establish the technical vision, engineering standards, and architectural roadmap for enterprise AI platforms and solutions.

• Serve as the senior technical leader for AI initiatives, providing architectural guidance, conducting design reviews, and driving key engineering decisions.

• Coach and develop engineers in system design, software engineering best practices, operational excellence, and professional growth.

• Partner with executive leadership to align AI investments, technology strategy, and delivery priorities with business objectives.

• Define and execute the strategy for enterprise AI, Generative AI, Agentic AI, and intelligent automation initiatives.

• Lead end-to-end solution delivery across the software development lifecycle, ensuring solutions meet business, performance, scalability, reliability, security, and cost objectives.

• Evaluate emerging AI technologies, platforms, and industry trends, recommending adoption strategies and architectural standards.

• Lead production support, incident response, and operational risk management for critical AI platforms and applications.

• Provide technical leadership for cloud-native AI platforms and applications across AWS, GCP, and enterprise ecosystems.

• Guide engineering teams in the design and implementation of: LLM and Generative AI solutions Retrieval-Augmented Generation (RAG) architectures Agentic AI and workflow orchestration platforms Serverless and event-driven architectures APIs, microservices, and platform services AI observability, evaluation, and monitoring frameworks

• Establish reusable engineering patterns, frameworks, and platform accelerators that improve scalability, reliability, and delivery velocity.

• Ensure AI solutions align with Responsible AI principles, enterprise technology standards, security controls, and regulatory requirements.

• Partner with security, privacy, legal, compliance, and risk teams to establish governance frameworks for AI development and deployment.

• Promote best practices for model evaluation, explainability, auditability, data protection, and operational risk management.

• Partner with product, engineering, data, security, compliance, and business stakeholders to define roadmaps and prioritize initiatives.

• Communicate complex technical concepts effectively to executive leadership, technical teams, and business partners.

• Serve as a trusted advisor and thought leader on enterprise AI strategy and adoption.

The successful candidate must possess demonstrated experience designing, delivering, and leading teams responsible for the following technologies and capabilities:

• Enterprise AI platforms including AWS Bedrock, GCP Vertex AI, Azure AI, or equivalent technologies.

• Cloud-native architectures leveraging serverless, event-driven, microservices, and API-based design patterns.

• Agentic AI frameworks including Bedrock Agents, Vertex AI Agent Builder, LangGraph, LangChain, LlamaIndex, Copilot Studio, and Power Automate.

• Multi-agent systems, workflow orchestration, tool integration, reasoning, and autonomous task execution.

• Enterprise RAG architectures, knowledge retrieval systems, vector search platforms, document ingestion pipelines, and enterprise data integration.

• Vector database technologies including OpenSearch, Pinecone, pgvector, FAISS, Milvus, or equivalent platforms.

• Model evaluation, fine-tuning, deployment, monitoring, observability, and optimization.

• AI platform scalability, governance, cost optimization, latency management, and operational excellence.

• Responsible AI governance, model documentation, risk management, validation, and auditability.

• Secure AI solution design aligned with healthcare, privacy, security, and regulatory requirements, including HIPAA.

• 7+ years of software engineering, platform engineering, machine learning, or AI engineering experience.

• 2+ years leading engineering teams or architecture initiatives, serving as a technical lead, solution architect, principal engineer, or engineering manager for enterprise-scale platforms.

• Proven experience designing, building, and operating cloud-native applications on AWS and/or GCP.

• Experience delivering production AI solutions, including Generative AI, Agentic AI, and Retrieval-Augmented Generation (RAG) platforms.

• Strong understanding of distributed systems, APIs, microservices, event-driven architectures, and modern software engineering practices.

• Experience partnering within a product operating model to define technology roadmaps and deliver business outcomes.

• Exceptional communication, mentorship, and technical leadership skills with the ability to influence both technical and executive audiences.

• Experience operating within Agile, Scrum, and/or SAFe delivery frameworks in large enterprise environments.

• Health Care Industry experience preferred.

The typical pay range for this role is: