[Hiring] AI/ML Engineer @UnitedHealth Group

Role Description

Are you passionate about applying AI to solve complex business challenges at enterprise scale? We are seeking an AI/ML Engineer to design, build, and operationalize AI capabilities that drive decision-making, productivity, and innovation across the Enterprise Finance organization. In this role, you will lead the development of AI-powered solutions including:

• Large language model (LLM) applications
• Retrieval-augmented generation (RAG)
• Intelligent agents
• Classification models
• Summarization workflows
• Decision-support tools

You will work closely with Finance, Data Engineering, Architecture, Security, and Responsible AI teams to deliver trusted, scalable, and governed AI solutions that align with enterprise AI/ML engineering practices and AI productization standards. You’ll enjoy the flexibility to work remotely from anywhere within the U.S. as you take on some tough challenges.

Primary Responsibilities:

• Design, develop, and deploy AI-powered solutions and architectures—including LLM workflows, prompt orchestration chains, agent-based solutions, RAG applications, and decision-support capabilities—to solve complex business challenges.
• Develop prompt strategies, grounding approaches, tool-calling patterns, guardrails, and fallback mechanisms to improve solution quality, safety, and reliability.
• Partner with Data Engineering teams to ensure access to trusted, governed, and high-quality enterprise data sources.
• Establish evaluation frameworks, test datasets, scoring rubrics, and model-performance benchmarks across AI deliverables.
• Monitor and optimize output quality, relevance, accuracy, consistency, latency, cost efficiency, and hallucination risk in production systems.
• Conduct failure-mode analysis, optimize model performance, and implement continuous improvements to AI systems.
• Collaborate cross-functionally with Quality Engineering, Responsible AI, Security, Privacy, Compliance, and Enterprise Architecture teams.
• Document AI solution behavior, limitations, risk controls, and operational monitoring requirements.
• Support production readiness through observability, monitoring, model evaluation, and drift detection practices.
• Evaluate emerging AI trends and leverage enterprise-approved AI tools to inform solution design, streamline workflows, and drive innovation.

You’ll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.

Qualifications

• 2+ years of experience in software engineering, machine learning, or AI engineering
• 1+ years of experience with cloud-native architecture, APIs, and scalable software systems

Requirements

• Master’s degree in Computer Science, Engineering, Data Science, or a related technical field (preferred)
• Experience supporting Finance, FP&A, Accounting, Treasury, Tax, or related enterprise corporate functions (preferred)
• Experience developing and deploying agentic AI solutions (preferred)
• Familiarity with AI observability, model monitoring, vector databases, semantic search, and knowledge retrieval systems (preferred)
• Experience developing enterprise AI products from conceptual design through production support (preferred)
• 1+ years of hands-on experience building and deploying generative AI and LLM-based applications in production environments (preferred)
• 1+ years of experience with prompt engineering, RAG architectures, AI agents, and model evaluation (preferred)
• 1+ years of experience applying Responsible AI, security, privacy, or compliance practices within engineering deliverables (preferred)

Benefits

• Comprehensive benefits package
• Incentive and recognition programs
• Equity stock purchase
• 401k contribution (all benefits are subject to eligibility requirements)

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.