• Translate business problems into clear analytical approaches and solution designs • Wrangle datasets and engineer features to support ML modeling and AI workflows • Build, evaluate, and iterate on ML models (forecasting, classification, optimization) • Support the development of LLM-based workflows and emerging agentic AI patterns as these initiatives ramp up • Contribute to deploying, monitoring, and maintaining AI and ML workflows in production, working closely with senior engineers • Stay curious about new AI development tools and frameworks, and bring them into our workflows where they fit

• Owning and defining the AI curriculum roadmap, including what is taught, what is prioritized, and what is removed as the landscape evolves • Conducting ongoing research and validation of emerging AI tools, models, and workflows to determine practical applications for founders and operators • Creating, documenting, and maintaining proprietary methodologies, frameworks, and intellectual property that can be consistently taught and scaled • Establishing and maintaining educational standards across AI-related curriculum and learning experiences • Teaching live and on camera alongside the Master Instructor in front of large student audiences • Translating complex AI concepts into actionable business strategies and implementation frameworks • Supporting the development of AI-powered coaching and advisory experiences to ensure consistency across student interactions • Partnering with internal stakeholders to continuously improve educational outcomes and student success • Staying at the forefront of AI advancements and evaluating their relevance to business owners and entrepreneurs.

Requisition Number: 2357751 Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care's most complex challenges. Your contributions here have the potential to change lives. Ready to build the next breakthrough? Join us to start Caring. Connecting. Growing together. As a Senior AI/ML Engineer within the Consumer Engineering division of the Chief Digital Office (CDO), you will play a critical role in shaping the future of our digital health platforms. This role is designed for a high-performing engineer with solid software fundamentals and a deep passion for building production-ready, scalable AI services. You will focus on the practical application of Generative AI techniques, designing end-to-end solutions that integrate seamlessly into our enterprise ecosystem. By leveraging modern data platforms and cloud-native architectures, you will help bridge the gap between complex machine learning research and reliable, consumer-facing applications that improve the lives of those we serve. 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: - Design, develop, and deploy AI-powered solutions to address complex business challenges with an emphasis on the responsible use of AI - Design, implement, and optimize AI and machine learning solutions, including statistical models, deep learning, and advanced Generative AI systems - Use enterprise-approved AI tools to streamline workflows, automate tasks, and drive continuous improvement across the engineering lifecycle - Build and operate large-scale training and inference pipelines using Databricks, PySpark, and cloud platforms (AWS, Azure, or GCP) - Apply advanced techniques such as RAG, LangChain, and Vector Databases to develop and scale Generative AI solutions - Execute proof-of-concepts and train models at scale, establishing performance baselines using quantitative evaluation metrics - Develop REST and FastAPI services, containerize solutions using Docker, and integrate UI tools to deliver seamless AI experiences - Evaluate emerging trends to inform solution design and lead strategic technical innovation within the team - Mentor junior engineers and lead design and architecture reviews to ensure high standards for code quality, safety, and reliability - Ensure solutions meet security, privacy, and regulatory standards, upholding ethical AI principles in every deployment 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 degree or equivalent experience - 5+ years of professional software engineering experience delivering high-quality, production-grade commercial applications - 3+ years of hands-on experience with Java, Python, and SQL - 2+ years of AI/ML engineering experience, including deploying models at scale and contributing to technical leadership - 1+ years of experience with cloud-native architectures (specifically AWS, Azure, or GCP) - 1+ years of experience with Databricks, PySpark, and data pipeline implementation - Experience with containerization (Docker) and building/maintaining CI/CD pipelines Preferred Qualifications: - Expertise in Generative AI solutions, specifically utilizing RAG, LangChain, and Vector Databases - Experience with big data technologies such as Spark, Hadoop, and Kafka - Proven solid knowledge of infrastructure as code (Terraform or CloudFormation) - Experience with data governance and platform-level controls (e.g., Unity Catalog, Delta Lake) - Demonstrated solid foundation in data science principles, including statistics, probability theory, and optimization *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 $120,100 to $214,500 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. At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission. UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations. UnitedHealth Group is a drug - free workplace. Candidates are required to pass a drug test before beginning employment. #BI-Hybrid

• Architect end-to-end integration solutions connecting internal AI co-worker platforms and enterprise data services with Salesforce Agentforce environments • Design scalable and secure distributed architectures across cloud-native enterprise ecosystems • Define integration blueprints using APIs, event-driven systems, and autonomous agent orchestration patterns • Design modular autonomous AI and micro-agent ecosystems to prevent overloaded reasoning engines • Establish governance standards for agent specialization, delegation boundaries, and semantic task routing • Evaluate and select optimal integration approaches, including REST APIs, gRPC services, event-driven architectures, and Model Context Protocol (MCP) • Build and integrate Salesforce-native AI capabilities using Invocable Apex methods, Advanced Salesforce Flows, and custom prompt templates • Enable intelligent workflows and autonomous execution capabilities within Salesforce ecosystems • Establish authentication boundaries, trust filters, and secure access controls for AI-driven enterprise workflows • Define data governance standards for sensitive enterprise information