We are seeking a highly skilled and motivated
Data Engineering Analyst with AI/ML expertise to drive the AI 10.0 initiative. This role blends deep expertise in data engineering, automation, and cloud-native development with hands-on experience in advanced AI/ML techniques, Large Language Models (LLMs), prompt engineering, and agentic frameworks. You will architect, build, and optimize intelligent data workflows, develop and fine-tune models, and collaborate across teams to deliver high-impact solutions for healthcare and insurance datasets.
You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office for a minimum of four days per week.
Primary Responsibilities:- Design and develop AI-driven solutions using LLMs to automate claims adjudication processes
- Build and optimize prompt engineering strategies for LLM-based applications
- Implement and integrate agentic frameworks to enable autonomous decision-making workflows
- Architect and deploy scalable data pipelines and AI workflows leveraging Python and related technologies
- Collaborate with cross-functional teams to ensure compliance with healthcare data standards and Responsible AI principles
- Contribute to model development, evaluation, and fine-tuning for production environments
- Mentor junior engineers and foster knowledge-sharing within the team
- Work independently to deliver innovative solutions aligned with business objectives
- 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.
Required Qualifications:- Bachelor's degree in CS or IT related field
- 5+ years of hands-on experience in data engineering and backend automation
- 5+ years of experience in Python, PySpark (Databricks), T-SQL, SQL, and big data technologies (Hadoop, Spark)
- 5+ years of experience with ETL tools, workflow orchestration (Airflow), and data warehousing (Snowflake or similar)
- 1+ years of experience in any one of the cloud technologies like Azure (ML Studio), AWS, GCP
- 1+ years of experience with CI/CD pipelines, GitHub Actions, and containerization tools (Docker)
- 1+ years of experience with Agile methodologies and DevOps practices
- 6+ months of experience with Generative AI frameworks/architectures (LangChain, HuggingFace, OpenAI APIs)
- 6+ months of experience with AI/ML concepts including Generative AI, LLMs (GPT, Gemini, LLaMA), and prompt engineering
Preferred Qualifications: - Understanding of Responsible AI principles and engineering best practices
- Familiarity with healthcare or health insurance domain data and compliance standards
- Excellent problem-solving skills and ability to handle ambiguity
*All Telecommuters will be required to adhere to UnitedHealth Group's Telecommuter Policy.
Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $72,800 to $130,000 annually based on full-time employment. We comply with all minimum wage laws as applicable.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.
