Staff AI Engineer

Generative AI Solutions 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.

Position Summary:

Design, build, and operationalize scalable, secure, and responsible Generative AI solutions across the affiliate line of business. In this role, you will work across AWS Bedrock, GCP Vertex AI, serverless compute, event-driven architectures, vector search, and agentic frameworks to deliver AI systems that accelerate business outcomes and improve experiences for our members, providers, and colleagues.

What You Will Do:

• Drives the development and implementation of advanced machine learning models and algorithms to solve complex healthcare problems, leveraging techniques such as predictive modeling, deep learning, and natural language processing.
• Collaborates with multiple departments, including data scientists, clinicians, and Information Technology (IT) professionals, to understand business requirements, define machine learning projects, and prioritize initiatives based on strategic objectives.
• Interfaces with stakeholders to define performance metrics and evaluation methodologies for machine learning models, contributing to rigorous testing, validation, and performance monitoring of models to ensure accuracy and reliability.
• Designs and implements scalable and efficient machine learning systems, including data pipelines, preprocessing, feature engineering, and model training, ensuring the quality and integrity of healthcare data used for analysis.
• Advises on the optimization and improvement of data pipelines, model training processes, and infrastructure to enhance efficiency, scalability, and performance of machine learning solutions.
• Consults on and presents technical findings, insights, and recommendations to both technical and non-technical stakeholders, contributing to the dissemination and application of machine learning insights in the healthcare industry.
• Ensures compliance with data privacy regulations, ethical guidelines, and industry standards in machine learning engineering, supporting the development of protocols and practices for model interpretability, fairness, and transparency.
• Manages team performance through regular, timely feedback as well as the formal performance review process to ensure delivery of exceptional services and engagement, motivation, and team development.
• Stays up-to-date with the latest advancements in machine learning and related technologies, continuously exploring and evaluating new algorithms and methodologies to enhance machine learning capabilities in healthcare applications.

AI & Cloud Engineering:

• Design, build, and deploy production-grade LLM and GenAI applications using the full breadth of AWS Bedrock and GCP Vertex AI capabilities (models, tuning, pipelines, vector search, guardrails, evaluation).
• Build cloud-native AI systems using:
• Serverless architectures (AWS Lambda, Step Functions, Event Bridge; Cloud Functions, Cloud Run)
• Event-driven architectures (SNS/SQS, Pub/Sub, Event Bridge, triggers)
• Microservices and APIs (Node.js, Java, Python)

Agentic Frameworks & Automation:

• Architect agentic AI systems using Bedrock Agents, Vertex AI Agent Builder, or approved frameworks (Lang Graph, Lang Chain, Llama Index Agents).
• Deliver multi-step reasoning, tool-use, and workflow orchestration for enterprise use cases.
• Comfortable designing and developing AI Agents using Copilot Studio and Cloud flow (Power Automate).

RAG Architectures:

• Develop robust Retrieval-Augmented Generation (RAG) systems using Bedrock Knowledge Bases, Vertex AI Vector Search, or custom vector databases (Open Search, Pinecone, FAISS, pgvector).
• Design document ingestion, embedding, chunking, grounding, and retrieval pipelines that integrate securely with enterprise data.

Model Lifecycle & Operationalization:

• Lead model experimentation, fine-tuning, evaluation, deployment, and monitoring across cloud platforms.
• Optimize cost, performance, token usage, latency, and scaling for production workloads.

Responsible AI & Compliance:

• Ensure all solutions meet CVS Health's Responsible AI standards, including model documentation, governance, risk assessment, and auditability.
• Design systems that adhere to HIPAA, data privacy, and security requirements.

Collaboration & Technical Leadership:

• Partner with product, engineering, data, security, and compliance teams to shape roadmaps and solution direction.
• Mentor engineers and contribute reusable patterns, frameworks, and platform accelerators.

Required Qualifications:

• 8+ years in large-scale software development
• 5+ years solution architecture or system design experience.
• 5+ years building large-scale…