Senior Software Engineer

UnitedHealth Group•Eden Prairie, MN

12h•Remote

About The Position

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by diversity and inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health equity on a global scale. Join us to start Caring. Connecting. Growing together. You will enjoy the flexibility to telecommute from anywhere within the U.S. as you take on some tough challenges. Software engineering is the application of engineering to the design, development, implementation, testing and maintenance of software in a systematic method. The roles in this function will cover all primary development activities across all technology functions that ensure we deliver code with high quality for our applications, products and services and to understand customer needs and to develop product roadmaps These roles include, but are not limited to analysis, design, coding, engineering, testing, debugging, standards, methods, tools analysis, documentation, research and development, maintenance, new development, operations and delivery. With every role in the company, each position has a requirement for building quality into every output This also includes evaluating new tools, new techniques, strategies; Automation of common tasks; build of common utilities to drive organizational efficiency with a passion around technology and solutions and influence of thought and leadership on future capabilities and opportunities to apply technology in new and innovative ways Reviews the work of others Develops innovative approaches Sought out as expert Serves as a leader/ mentor Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI You’ll be rewarded and recognized for your performance in an environment that will challenge you and give you clear directions on what it takes to succeed in your role as well as provide development for other roles you may be interested in.

Requirements

Bachelor’s degree in Computer Science or equivalent program
5+ years of Azure cloud experience
2+ years of AI experience
2+ years of AI experience, LLMs, embeddings, RAG, fine-tuning, evaluation
Familiarity with Hugging Face and LangChain/LlamaIndex

Nice To Haves

Strong foundation in machine learning, statistics, optimization, and probability
Hands‑on experience with: Classical ML, deep learning, and Generative AI models
Model evaluation, validation, and performance tuning
Proficiency in Python and modern AI libraries
Experience with RAG frameworks, vector databases, LangChain / LangGraph‑style orchestration
Solid foundation in statistics and ML (hypothesis testing, experimental design, feature engineering, supervised/unsupervised methods)
Experience building scalable, cloud‑native AI systems (Azure)
Strong software engineering practices: GitHub, code reviews, CI/CD

Responsibilities

Lead architecture and delivery of ML/GenAI solutions (classification, forecasting, NLP, deep learning, LLM apps) at production scale
Build robust data/feature pipelines over large clinical/claims datasets; write efficient, well-tested Python (pandas/NumPy) and SQL
Develop and deploy LLM capabilities: prompt design, fine-tuning, RAG pipelines, vector indexing, and evaluation with guardrails
Work closely with lead engineers to develop the best technical design and approach for new product development
Collaborates closely with Business Analysts on developing requirements and may assist with estimating
Instill best practices for software development and documentation, assure designs meet requirements, and deliver high-quality work on tight schedules
Translate business requirements into technical solutions, recommend alternative technical and business approaches, and lead engineering efforts to meet aggressive timelines with optimal solutions
Operational Excellence – build, deploy, monitor, and operation of production services
Establish LLMOps best practices: CI/CD, model registry, experiment tracking, monitoring, drift detection, A/B testing, cost/perf optimization