Senior Software Development Engineer

CVS Health•Irving, TX

About The Position

The Senior Software Engineer will design, build, and ship production-grade AI-powered products and the software and data foundations behind them. Working with engineering, analysts, data scientists, and product teams in a fast-paced, agile environment, the role uses AI/ML and GenAI to reimagine healthcare delivery. It spans the full lifecycle of an AI solution, including data pipelines, feature and vector stores, LLM-powered backend services and agentic workflows, and user-facing applications built on cloud-native, AI-ready architectures. The position calls for extensive knowledge of modern programming languages and frameworks and experience developing full-stack and data solutions that support production-scale machine learning and generative AI use cases.

Requirements

  • At least 6 years of professional software engineering experience, including strong full-stack application development experience and a track record of delivering AI/ML-enabled solutions to production.
  • Proficiency in at least one modern backend language, such as Python, Java, or Node.js/TypeScript, and one modern front-end framework, such as React, Angular, or Vue.
  • Hands-on experience building and deploying agentic AI solutions in complex cloud infrastructure environments, including orchestration frameworks such as LangChain or LangGraph and integration with LLM APIs.
  • Experience building data pipelines for ML/AI workloads, including feature engineering, embedding generation, and integration with vector databases for RAG use cases.
  • Experience designing and building RESTful APIs and microservices, including authentication and authorization, API security, service-to-service integration, and serving AI/LLM capabilities through APIs.
  • At least 6 years of experience with SQL and relational database management systems, including schema design and query optimization.
  • At least 3 years of experience with cloud platforms and data engineering platforms such as AWS, GCP, Azure, Databricks, or Snowflake.
  • Familiarity with MLOps/LLMOps practices, model versioning, monitoring, and production ML/AI pipeline support.
  • Experience with CI/CD, containerization (Docker, Kubernetes), Git-based workflows, and automated testing.
  • Hands-on experience troubleshooting data, application, and AI system issues.
  • Hands-on experience with performance improvement techniques across data, backend, front end, and AI inference layers.
  • Willingness to identify and implement process improvements and best practices, and ability to take ownership in a fast-paced, collaborative, team-based environment.
  • Excellent oral and written communication skills, including the ability to explain complex technical and AI concepts to nontechnical stakeholders.
  • Bachelor’s degree in Computer Science, Engineering, or a related field.

Nice To Haves

  • Familiarity with healthcare data and healthcare insurance feeds.
  • Experience building conversational or GenAI-enabled user interfaces, such as chat or copilot experiences.
  • Experience with prompt engineering, model evaluation frameworks (such as LLM-as-judge or golden datasets), and techniques such as fine-tuning or model optimization.
  • Exposure to AI governance and responsible AI practices in a regulated environment such as healthcare.
  • Experience with event-driven and streaming architectures such as Kafka or Pub/Sub.
  • Experience with infrastructure as code such as Terraform and observability tooling for applications and AI systems.
  • Experience using AI coding assistants and agentic developer tools in day-to-day engineering.

Responsibilities

  • Design, build, and deploy agentic AI systems and LLM-powered applications, including multistep workflows, tool use, and orchestration with frameworks such as LangChain and LangGraph.
  • Develop end-to-end retrieval-augmented generation (RAG) solutions, including ingestion, chunking, embedding generation, vector indexing, retrieval tuning, and grounding model responses.
  • Design, build, and maintain data pipelines, data models, feature stores, and vector stores for analytics, ML, and GenAI workloads.
  • Build full-stack applications that expose AI capabilities to users, including responsive front-end interfaces, backend services, and RESTful or GraphQL APIs.
  • Integrate applications with LLM APIs, relational databases, data platforms, and vector databases; optimize data access patterns, latency, and token or inference cost.
  • Implement MLOps/LLMOps practices, including model and prompt versioning, evaluation pipelines, quality, drift, and hallucination monitoring, and automated release workflows.
  • Implement CI/CD pipelines, automated testing, infrastructure as code, and observability across applications, data pipelines, and AI services.
  • Troubleshoot and resolve production issues across data quality, model behavior, API performance, and user interfaces.
  • Apply AI-assisted development tools to improve productivity, code quality, and delivery speed, and help establish team standards for their use.
  • Participate in design and code reviews, mentor junior engineers, and champion engineering and AI best practices.
  • Partner with product owners, designers, analysts, and data scientists to translate business needs into AI-enabled technical solutions.
  • Ensure solutions meet security, privacy, and compliance standards, including HIPAA, and apply responsible AI practices such as guardrails, PHI/PII protection, auditability, and human-in-the-loop controls.

Benefits

  • Medical coverage
  • Dental coverage
  • Vision coverage
  • Paid time off
  • Retirement savings options
  • Wellness programs
  • Other resources to support physical, emotional, and financial well-being, based on eligibility
  • Eligible for a CVS Health bonus, commission, or short-term incentive program
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