Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.
Primary Responsibilities:
- Design, develop, train, evaluate, deploy, and scale Machine Learning and Generative AI solutions for enterprise business use cases
- Develop and implement advanced AI capabilities including NLP, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, and intelligent automation solutions
- Optimize AI models and applications for performance, scalability, reliability, explainability, and maintainability
- Evaluate emerging AI technologies and recommend adoption strategies aligned with business objectives
- Translate complex business requirements into AI-driven solutions that deliver measurable outcomes
- Partner with data engineering teams to design and build robust data pipelines supporting AI and analytics initiatives
- Work with structured, semi-structured, and unstructured data to improve model accuracy and business insights
- Perform exploratory data analysis, feature engineering, and data quality assessments
- Identify trends, patterns, and opportunities that drive continuous model improvement and business decision-making
- Develop APIs, microservices, AI services, and integrations for seamless deployment of AI models into production environments
- Implement and maintain MLOps best practices, including CI/CD pipelines, model versioning, automated testing, deployment automation, and monitoring
- Collaborate with software engineering and platform teams to ensure AI solutions are secure, scalable, resilient, and operationally efficient
- Build reusable AI frameworks, accelerators, templates, and engineering standards to improve organizational productivity
- Monitor and maintain production AI solutions to ensure reliability and performance
- Establish model governance, validation, monitoring, and lifecycle management processes
- Apply Responsible AI principles including fairness, transparency, explainability, privacy protection, and bias mitigation
- Monitor model drift, performance degradation, and operational risks through observability frameworks
- Ensure compliance with enterprise security, regulatory, and governance requirements
- Partner with product managers, architects, engineers, business stakeholders, and data teams to define and deliver AI-driven solutions
- Lead technical discussions, architectural reviews, design sessions, and solution planning activities
- Mentor engineers and promote AI/ML best practices, engineering excellence, and technical growth
- Communicate technical concepts, risks, recommendations, and business impact effectively to technical and non-technical audiences
- Collaborate with cross-functional teams to achieve project and organizational objectives
- Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so
Required Qualifications:
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related field
- 5+ years of professional experience developing, deploying, and supporting AI/ML solutions in enterprise environments
- Experience building and deploying machine learning models into production environments
- Experience developing APIs, microservices, and scalable cloud-native applications
- Experience with Agile, Scrum, and modern software development methodologies
- Knowledge of CI/CD pipelines, software testing, observability, version control, and secure software development practices
- Solid understanding of supervised learning, unsupervised learning, deep learning, NLP, LLMs, feature engineering, experimentation, and model evaluation techniques
- Solid proficiency in Python and experience with AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, LangChain, Semantic Kernel, Hugging Face, or similar technologies
- Proven solid analytical, problem-solving, communication, and stakeholder management skills
- Demonstrated ability to work independently while collaborating effectively across multiple teams
Preferred Qualifications:
- AI/ML, Cloud, Data Science, or Responsible AI certifications
- Experience mentoring engineers or leading AI/ML initiatives across multiple teams
- Experience with Generative AI platforms such as Azure OpenAI, OpenAI, Anthropic, Google Vertex AI, or equivalent enterprise AI services
- Experience implementing RAG architectures, vector databases, AI agents, prompt engineering, semantic search, and conversational AI applications
- Hands-on experience with MLOps platforms such as Azure ML, Databricks, MLflow, Kubeflow, SageMaker, or similar technologies
- Experience in healthcare, claims processing, automation, operations, compliance, or regulated industries
- Knowledge of distributed computing technologies such as Spark, Kafka, and enterprise-scale data platforms
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.