Requisition Number: 2345319 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. Optum Insight partners with payers, providers, governments and life sciences companies to simplify and enhance clinical, administrative and financial processes through software-enabled services and analytics, while advancing value-based care. Our differentiated products, technology insights, clinical expertise and analytics support the entire health system - ultimately delivering better experiences for consumers. Optum Insight Technology and Engineering is a critical function in Optum Insight driving the innovation and value we provide our customers and partners. This team is focused on products, solutions, platform / enabling capability development, product development lifecycle, engineering excellence and connectivity to Optum Technology. The Clinical Decision Support (CDS) Engineering team, a unit within the Optum Insight Technology organization is responsible for building commercial products helping payers and providers with administrative and clinician focused CDS solutions. We are seeking a lead AI/ML engineer who can bring deep expertise across the full development lifecycle of machine learning and generative AI-based solutions from design to development to MLOps. CDS is an area that truly touches payers, providers, as well as members and one where you can have a huge impact on improving the healthcare system for everyone. 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: - Drive end-to-end generative AI and machine learning projects that have a high degree of ambiguity, scale, and complexity - Design robust AI architectures, ensuring that systems are scalable, secure, and efficient; select appropriate technologies, frameworks, and methodologies - Build machine learning models; perform proof-of-concept experiments; optimize and deploy models to production; partner with software engineers to productionize ML models - Perform hands-on analysis and modeling of healthcare data sets to develop insights that increase business value - Run A/B experiments, gather data, and perform statistical analysis; continuously assess AI system performance and optimize algorithms and models to improve accuracy and efficiency - Establish scalable, efficient, automated processes for large-scale data analysis, machine learning model development and validation, and MLOps - Research and implement innovative machine learning approaches - Mentor and help recruit AI/ML scientists and machine learning engineers to the team 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 in Computer Science or a related field - 10+ years of industry/academic experience in machine learning or a related field - 5+ years of experience building models for business applications - 5+ years of experience leading technical teams - Proven advanced understanding of Deep Learning with applications in NLP and multimodal modeling - Proven solid Python programming skills and experience with deep learning frameworks such as PyTorch or TensorFlow and big data processing tools like Hadoop and Spark - Practical experience with AI technology stacks and deployment and operations methodologies in public cloud (Microsoft Azure technology stack preferred) - Experience with state-of-the-art ML algorithms and architectures (e.g., Transformers/LLMs, state space models such as Mamba, GNNs), including hands-on transformer fine-tuning, legacy architecture maintenance/migration, and tradeoffs between pretraining from scratch vs. adapting existing foundations - Proven in-depth knowledge of generative AI and large language models (LLMs), with a focus on LLM optimization - Solid experience working with unstructured text at scale (e.g., clinical notes, documents, policies, or similar natural-language-heavy domains) Preferred Qualifications: - Experience applying AI/ML in the health care sector - Experience working with cross-functional and distributed teams in a global and diverse environment - Experience establishing AI/ML best practices, standards, and ethical guidelines - Proven solid communication skills to articulate technical concepts to engineers and non-technical stakeholders *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 $91,700 to $163,700 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. #letsgrow

• Design and build next-generation AI systems • Architect RAG pipelines for AI • Develop agentic workflows for multi-step tasks • Ensure reliability and ethical safety of models • Collaborate with DevOps for deployment in cloud environments

• Design and oversee the development of scalable generative AI systems and enterprise-grade AI platforms. • Establish robust architectures that support model training, inference, monitoring, and lifecycle management in production environments. • Direct the selection, customization, and enhancement of state-of-the-art generative AI and large language models. • Develop and execute APIs, microservices, and integration frameworks to incorporate AI capabilities into enterprise applications. • Ensure that AI platforms meet stringent standards for performance, reliability, security, and scalability, while also adhering to data governance and privacy regulations. • Collaborate closely with product, engineering, and business teams to outline technical requirements and approaches to AI architecture. • Architect end-to-end pipelines for deploying and monitoring AI models, ensuring seamless integration with existing systems. • Guide architectural decisions for LLM applications, AI workflows, and distributed AI infrastructure. • Institute best practices for ethical AI development, including strategies to mitigate risks like model hallucinations, bias, and reliability challenges. • Provide technical mentorship and guidance to engineering teams, while contributing to the formulation of long-term technology strategies and the advancement of AI platforms.

• Design and implement an AI orchestration layer integrated into the CI/CD pipeline. • Orchestrate AI agents and skills across all stages of the SDLC (design, development, testing, refactoring). • Define how AI sessions are created, managed, versioned, audited, and reviewed. • Design mechanisms to automatically provision per-project context. • Automate workflows from Jira tickets. • Embed AI orchestration into CI/CD pipelines. • Lead the initial deployment of Devin across the organization. • Define metrics to measure AI's impact on productivity, quality, and reliability. • Ensure all AI activity is observable, auditable, and aligned with corporate governance. • Act as the technical owner for AI within the SDLC.