The Lead AI/ML Engineer is a strategic and hands on technical leader responsible for designing, building, and deploying advanced AI and machine learning solutions across the full application stack. This role blends deep expertise in AI/ML, cloud native architectures, and full stack software engineering with cross functional leadership, driving innovation, operational excellence, and scalable AI adoption across the organization.
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 a minimum of four days per week.
Primary Responsibilities:- Model Development & Deployment
- Architect, develop, and deploy scalable AI/ML platforms and full stack application solutions, spanning model training, inference, APIs, and user experiences
- Implement AI/ML computing infrastructures and application stacks using frameworks such as AWS Bedrock core/Google ADK, with orchestration using AWS AgentCore for multi agent workflows
- Design end to end pipelines covering data ingestion, feature processing, model serving, and observability
- Full Stack Engineering
- Build and maintain production grade backend services and APIs using Java and Python
- Develop and integrate frontend and lightweight UI components (eg, dashboards, internal tools) to operationalize AI workflows and analytics
- Apply modern software engineering practices including CI/CD pipelines, containerization, and cloud native deployment
- Cross functional Collaboration
- Partner closely with data scientists, product managers, UX teams, and business stakeholders to translate complex business requirements into scalable AI and full stack solutions
- Act as a bridge between research, engineering, and product teams to ensure solutions are practical, performant, and maintainable
- AI Strategy & Governance
- Define and document architecture roadmaps, reference architectures, and standard operating procedures for AI/ML systems
- Ensure alignment with enterprise standards for reliability, security, fairness, transparency, and regulatory compliance
- Technical Leadership & Mentorship
- Lead technical design reviews, guide architectural decisions, and oversee model evaluation, optimization, and deployment cycles
- Mentor junior and senior engineers, setting clear expectations for code quality, system design, and operational readiness
- Innovation & Research
- Conduct applied research to advance capabilities in Generative AI, NLP, NLU, computer vision, and predictive modeling
- Stay current with emerging tools, architectures, and industry trends, and translate them into actionable engineering practices
- Operational Excellence
- Lead disaster recovery and business continuity planning for AI and application infrastructure
- Monitor, tune, and continuously improve deployed models and services for performance, accuracy, scalability, and cost efficiency
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.
Required Qualifications:- Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical field
- 9+ years of professional software engineering experience, with demonstrated success designing and delivering high quality, commercial full stack applications in production environments
- 6+ years of hands on proficiency in Java, Python, SQL, and Linux shell scripting, with production experience in distributed systems
- 5+ years of AI/ML engineering experience, including deploying models at scale and leading or mentoring technical teams
- 4+ years of Solid cloud experience in various CSPs ( especially AWS)
- 2+ years of applied AI/ML experience, including deep learning, NLP/NLU, semantic nderstanding, intent classification, ASR, predictive modeling, and time series analysis
- 2+ years of experience in MongoDB and MLOps
- Technical Experience:
- Proven cloud experience with Google Cloud (Vertex AI) and working knowledge of AWS, including cloud native architectures, containerization, and orchestration
- Hands on experience with Hadoop ecosystems, and MLOps practices for model lifecycle management
- Experience integrating AI/ML models into end to end, user facing applications
- Solid understanding of API based architectures, distributed data systems, and scalable backend services
- Must be authorized to work in the United States without the need for current or future employer-sponsored visa sponsorship (e.g., H-1B, TN, F-1/OPT, CPT, or other employment-based visa status)
Preferred Qualifications:- Experience working in enterprise or regulated environments with governance and compliance requirements
- Data Science Foundations: Solid grounding in statistics, probability theory, optimization, simulation, and data modeling
- Communication & Influence: Ability to clearly present complex analytical and AI concepts to both technical and non technical audiences
What Success Looks Like in This Role- AI/ML solutions are production ready, scalable, and fully integrated into full stack applications
- Teams are aligned on clear architectures, standards, and best practices
- Engineers are mentored effectively, and delivery velocity improves without sacrificing quality or reliability
- AI systems demonstrate measurable business impact, operational stability, and trustworthiness
*All employees working remotely 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 $145,500 - $249,500 annually based on full-time employment. We comply with all minimum wage laws as applicable.
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.
