Staff Software Development Engineer (Agentic AI/ML)

CVS Health•Richardson, MA

4d•$118,450 - $260,590•Remote

About The Position

CVS Health is seeking a Staff Software Engineer with a strong background in enterprise software architecture, full-stack application development, and building cloud-native and Agentic AI/Gen AI products. This role will serve as a senior technical leader and a hands-on engineer responsible for designing, building, and modernizing mission-critical technology solutions for the Claims Adjudication organization. The ideal candidate will have expertise in enterprise software engineering, a strong architecture background, hands-on programming experience, and practical experience building production-grade Generative AI and Agentic AI solutions. This role will be instrumental in advancing CVS Health’s transition toward modern, AI-driven, cloud-native platforms while ensuring continued reliability and integration with existing legacy systems such as IBMi/AS400. This role requires a strong balance of technical strategy, architecture leadership, hands-on coding, engineering execution, stakeholder communication, and production operational excellence. We will consider remote US for the right candidate.

Requirements

7+ years of software engineering experience, including significant experience designing and building enterprise-scale software systems including:
Strong architecture experience across distributed systems, micro services, APIs, event-driven architecture, domain-driven design, and cloud-native platforms.
Hands-on experience building applications in Python, Java , React and other open source frameworks.
2+ years of experience designing or implementing Generative AI, Agentic AI, LLM-based, or AI/ML-enabled applications.
Experience with Enterprise RAG patterns, vector databases, embeddings, prompt engineering, AI orchestration, and AI application integration.
Experience implementing CI/CD pipelines and DevSecOps practices using tools such as Azure DevOps, GitHub Actions, Jenkins, GitLab CI/CD, or equivalent.
Exposure to observability practices including logging, tracing, monitoring, reporting and production troubleshooting.
Strong verbal and written communication skills with the ability to influence technical and non-technical stakeholders.
Experience leading complex technical initiatives, setting technical direction, mentoring engineers, and driving execution across teams.
Bachelor’s degree or equivalent experience

Nice To Haves

10+ years leading concurrent technical projects in both legacy IBMi/AS400 or similar and emerging technologies.
Experience leading complex technical initiatives, setting technical direction, mentoring engineers, and driving execution across teams.
Health care industry domain knowledge.
Experience with RxClaim or other PBM adjudication systems.
Experience with Agentic AI frameworks such as Semantic Kernel, LangGraph, LangChain, AutoGen, CrewAI, or equivalent.
Experience leading enterprise AI transformation initiatives, establishing AI engineering best practices, and defining standards for Agentic AI and Generative AI adoption.
Experience designing and implementing AI Agents using tool calling, reasoning frameworks, workflow orchestration, multi-agent systems, and autonomous execution patterns.

Responsibilities

Lead the architecture, design, and implementation of scalable, secure, resilient, and maintainable enterprise software solutions.
Establish architecture principles, design patterns, reference architectures, engineering standards, and technical guardrails.
Lead architecture reviews, design discussions, and technical decision-making forums with engineering teams, architects, product partners, and leadership.
Design, develop, and deploy cloud-native solutions such as API, micro services, CI/CD pipelines and real-time streaming on public cloud platforms, preferably Azure or GCP.
Remain actively hands-on in software design, coding, code reviews, debugging, troubleshooting.
Design, implement, and improve CI/CD pipelines for automated build, test, security scanning, deployment, and release management.
Partner with business and technology teams to identify high-value AI use cases and translate them into scalable technical solutions.
Design, build, and deploy enterprise-grade Agentic AI and Generative AI solutions translating SDLC to ADLC.
Support model evaluation, prompt evaluation, response quality assessment, guardrails, responsible AI practices, and AI governance.
Integrate LLMs, AI/ML models, vector stores, orchestration frameworks, and cloud-native services into enterprise applications.
Communicate complex technical concepts clearly to engineering teams, architects, product owners, business stakeholders, and senior leadership.
Partner with cross-functional teams to align technology execution with business outcomes.