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The Role
Leads end-to-end AI/ML solution delivery, including model development, generative AI, LLMs, RAG, APIs, user interfaces, MLOps, LLMOps, monitoring, responsible AI, and production support. Provides architecture leadership, mentors engineers, collaborates with cross-functional stakeholders, and ensures scalable, secure, compliant, and maintainable solutions.
Summary Generated by Built In
Requisition Number: 2390917
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:
Required Qualifications:
Preferred Qualifications:
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.
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:
- Lead the end-to-end design and delivery of AI/ML solutions, from business problem framing, data preparation, experimentation, and model development to production deployment and support
- Develop and apply machine learning, deep learning, natural language processing, computer vision, and generative AI techniques based on the needs of the use case
- Build, fine-tune, evaluate, optimize, and integrate predictive models, large language models, retrieval-augmented generation (RAG) solutions, and AI agents
- Design secure, scalable, and well-documented REST APIs and microservices using Python frameworks such as FastAPI or Flask to expose AI capabilities to enterprise applications
- Design and develop responsive web-based user interfaces using modern front-end frameworks such as React or Angular; integrate UI workflows with AI services and APIs
- Establish model evaluation approaches using appropriate metrics such as precision, recall, F1 score, ROC-AUC, latency, throughput, groundedness, relevance, and quality measures based on the solution type
- Implement MLOps and LLMOps practices for experiment tracking, model versioning, automated testing, CI/CD, deployment, monitoring, drift detection, observability, and controlled rollback
- Create reusable AI components, reference architectures, coding standards, engineering guardrails, and technical documentation to accelerate delivery across the team
- Lead architecture and design discussions; select fit-for-purpose technologies and make informed trade-offs across model quality, scalability, security, maintainability, performance, and cost
- Partner with Product Management, business stakeholders, data scientists, data engineers, architects, security teams, and platform teams for backlog refinement, planning, estimation, and delivery
- Lead and mentor AI/ML and full-stack engineers through technical direction, code reviews, design reviews, pair programming, troubleshooting, and engineering best practices
- Ensure responsible AI practices, human oversight, privacy, security, explainability, bias assessment, auditability, and compliance requirements are incorporated throughout the solution lifecycle
- Investigate complex production issues across data pipelines, models, APIs, UI, cloud infrastructure, and integrations; drive root-cause analysis and sustainable corrective actions
- Communicate technical concepts, solution risks, model limitations, outcomes, and recommendations clearly to engineering teams, business partners, and leadership
- Work effectively and demonstrate ownership, collaboration, sound judgment, adaptability, and a delivery-focused mindset
- Comply with all applicable Company policies, procedures, and business directives, changes including those relating to work location, team assignments, work schedules, and flexible work arrangements
Required Qualifications:
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related technical discipline
- 8+ years of overall software engineering experience, including significant hands-on experience delivering AI/ML solutions and providing technical leadership to engineering teams
- Hands-on experience with deep learning architectures and frameworks such as PyTorch or TensorFlow, including neural networks, transformers, embeddings, and model optimization techniques
- Hands-on Python development experience and proficiency with AI/ML libraries such as scikit-learn, pandas, NumPy or equivalent technologies
- Experience developing generative AI solutions using large language models, prompt engineering, RAG, vector databases, semantic search, orchestration frameworks such as Lang Chain or Semantic Kernel, and model evaluation techniques
- Experience designing secure REST APIs and production microservices using FastAPI, Flask, or equivalent frameworks, including authentication, authorization, validation, error handling, logging, and API documentation
- Experience with cloud-based AI and data platforms such as Microsoft Azure, Azure AI Foundry/Azure OpenAI, Azure Machine Learning, Databricks, or comparable platforms
- Experience with SQL and relational or NoSQL databases; understanding of data ingestion, transformation, data quality, and model-ready dataset creation
- Experience using GitHub, GitHub Actions, Docker, automated testing, code scanning, and CI/CD practices for AI and application development
- Experience deploying and monitoring scalable model-training and inference workloads, including batch and real-time patterns
- Solid understanding of supervised and unsupervised learning, feature engineering, model selection, validation, hyperparameter tuning, dimensionality reduction, classification, regression, clustering, and time-series or anomaly-detection approaches
- Proven ability to lead technical teams, decompose complex problems, estimate work, manage technical dependencies, mentor engineers, and drive delivery across the full software development lifecycle
- Solid analytical, problem-solving, decision-making, written communication, verbal communication, and stakeholder-management skills
Preferred Qualifications:
- Experience with Kubernetes, cloud-native deployment, infrastructure as code, and enterprise observability tools
- Experience with MLflow, Azure Machine Learning, Databricks, feature stores, model registries, vector databases, or comparable MLOps/LLMOps platforms
- Experience designing agentic AI workflows, tool/function calling, multi-agent patterns, and human-in-the-loop controls
- Experience with responsible AI governance, explain ability, fairness, privacy, security, and risk controls in regulated environments
- Healthcare domain experience and familiarity with handling sensitive or regulated data
- Experience leading proofs of concept and converting successful prototypes into secure, supportable, production-grade solutions
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.
Skills Required
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related technical discipline
- 8+ years of overall software engineering experience, including significant hands-on AI/ML delivery and technical leadership
- Hands-on experience with deep learning architectures and PyTorch or TensorFlow
- Hands-on Python development and proficiency with scikit-learn, pandas, NumPy, or equivalent technologies
- Experience developing generative AI solutions using LLMs, prompt engineering, RAG, vector databases, semantic search, orchestration frameworks, and model evaluation
- Experience designing secure REST APIs and production microservices using FastAPI, Flask, or equivalent frameworks
- Experience with cloud-based AI and data platforms such as Azure, Azure OpenAI, Azure Machine Learning, or Databricks
- Experience with SQL and relational or NoSQL databases, data ingestion, transformation, data quality, and model-ready dataset creation
- Experience using GitHub, GitHub Actions, Docker, automated testing, code scanning, and CI/CD practices
- Experience deploying and monitoring scalable model-training and inference workloads
- Understanding of supervised and unsupervised learning, feature engineering, model selection, validation, tuning, classification, regression, clustering, and time-series or anomaly detection
- Ability to lead technical teams, decompose complex problems, estimate work, manage dependencies, mentor engineers, and drive SDLC delivery
- Strong analytical, problem-solving, decision-making, communication, and stakeholder-management skills
- Experience with Kubernetes, cloud-native deployment, infrastructure as code, and enterprise observability tools
- Experience with MLflow, Azure Machine Learning, Databricks, feature stores, model registries, vector databases, or comparable MLOps/LLMOps platforms
- Experience designing agentic AI workflows, tool or function calling, multi-agent patterns, and human-in-the-loop controls
- Experience with responsible AI governance, explainability, fairness, privacy, security, and risk controls in regulated environments
- Healthcare domain experience and familiarity with sensitive or regulated data
- Experience leading proofs of concept and converting prototypes into secure, supportable, production-grade solutions
Optum Compensation & Benefits Highlights
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Leave & Time Off Breadth — PTO is generally described as decent or good, and many note it as a strong part of the package. Actual ability to take time off can depend on workload and team coverage.
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Retirement Support — Offerings include a 401(k) with employer match and access to an employee stock purchase plan, which are highlighted as meaningful components of total rewards. These programs are consistently referenced among core benefits.
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Parental & Family Support — Parental and caregiver leave, along with adoption assistance, are publicly highlighted and viewed as notable elements of the package. Availability can be role-specific, but these supports contribute to overall breadth where offered.
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The Company
What We Do
Optum, part of the UnitedHealth Group family of businesses, 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. At Optum, we support your well-being with an understanding team, extensive benefits and rewarding opportunities. By joining us, you’ll have the resources to drive system transformation while we help you take care of your future. We recognize the power of connection to drive change, improve efficiency and make a difference in health care. Join a team where your skills and ideas can make an impact and where collaboration is key to creating technology that produces healthier outcomes.
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Optum Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
Optum has three workplace models that balance the needs of the business and the responsibilities of each role. These models, core on‑site (5 days/week), hybrid (4 days/week) and telecommute or fully remote, vary by country, role and location.
Typical time on-site:
Not Specified
