Staff AI Engineer

CVS Health

3d•$106,605 - $260,590

About The Position

Design, build, and operationalize scalable, secure, and responsible Generative AI solutions across the affiliate line of business. The role spans AWS Bedrock, GCP Vertex AI, serverless computing, event-driven architectures, vector search, and agentic frameworks to deliver AI systems that accelerate business outcomes and improve experiences for members, providers, and colleagues. It combines hands-on engineering with architecture, platform leadership, and cross-functional collaboration in a HIPAA-regulated environment. The Staff AI Engineer develops production-grade LLM and Generative AI applications, cloud-native AI systems, agentic workflows, and Retrieval-Augmented Generation (RAG) solutions. The role leads model experimentation, fine-tuning, evaluation, deployment, and monitoring, while optimizing cost, performance, token usage, latency, and scaling. It also ensures responsible AI practices, governance, risk assessment, auditability, privacy, and security requirements are met. The position partners with product, engineering, data, security, and compliance teams to shape roadmaps and solution direction, mentors engineers, and contributes reusable patterns, frameworks, and platform accelerators. It also drives machine-learning initiatives for healthcare, collaborates with clinicians and other stakeholders, monitors model quality and performance, and supports team development.

Requirements

7+ years of experience in large-scale software development.
5+ years of solution architecture or system design experience.
5+ years building large-scale microservices or APIs using Node.js.
3+ years of hands-on experience with GCP and AWS, including serverless, event-driven, AI/ML, and CI/CD.
Experience with AWS Bedrock, GCP Vertex AI, or similar technologies.
Strong communication and leadership skills.
Strong experience with Python for AI/ML engineering.
Production experience with agentic AI frameworks.
Production experience with RAG architectures and vector databases.
Production experience with serverless and event-driven designs.
Bachelor’s degree or equivalent experience; equivalent experience is defined as a high school diploma plus 4 years of relevant experience.

Nice To Haves

Experience with Vertex AI Generative AI Studio, vector search orchestration, and agent capabilities.
Hands-on experience with vector databases such as OpenSearch, Pinecone, FAISS, pgvector, or Milvus.
Strong knowledge of prompt engineering, evaluation, observability, and LLM security patterns.
Ability to write clear design documents, architectural diagrams, runbooks, and technical briefs.
Agile/SAFe experience in large enterprises.
AWS or GCP cloud certifications.

Responsibilities

Drive development and implementation of advanced machine-learning models and algorithms for complex healthcare problems, including predictive modeling, deep learning, and natural language processing.
Collaborate with data scientists, clinicians, IT professionals, and other departments to understand business requirements, define projects, and prioritize initiatives.
Define model performance metrics and evaluation methodologies with stakeholders; support testing, validation, and performance monitoring.
Design and implement scalable machine-learning systems, including data pipelines, preprocessing, feature engineering, and model training, while ensuring healthcare data quality and integrity.
Advise on improving data pipelines, model training processes, and infrastructure to increase efficiency, scalability, and performance.
Present technical findings, insights, and recommendations to technical and non-technical stakeholders.
Ensure compliance with privacy regulations, ethical guidelines, and industry standards, including practices for model interpretability, fairness, and transparency.
Manage team performance through timely feedback and formal performance reviews, supporting service delivery, engagement, motivation, and team development.
Stay current with machine-learning advancements and evaluate algorithms and methodologies relevant to healthcare.
Design, build, and deploy production-grade LLM and Generative AI applications using AWS Bedrock and GCP Vertex AI capabilities.
Build cloud-native AI systems using serverless architectures, event-driven architectures, microservices, and APIs.
Architect agentic AI systems and deliver multi-step reasoning, tool use, and workflow orchestration for enterprise use cases.
Design and develop AI agents using Copilot Studio and Power Automate cloud flows.
Develop RAG systems and secure document ingestion, embedding, chunking, grounding, and retrieval pipelines integrated with enterprise data.
Lead model experimentation, fine-tuning, evaluation, deployment, and monitoring across cloud platforms.
Optimize production workloads for cost, performance, token usage, latency, and scaling.
Meet CVS Health Responsible AI standards, including model documentation, governance, risk assessment, and auditability.
Design systems that adhere to HIPAA, data privacy, and security requirements.
Partner with product, engineering, data, security, and compliance teams on roadmaps and solution direction.
Mentor engineers and contribute reusable patterns, frameworks, and platform accelerators.