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.

Role Summary

The Principal Software Engineer is a senior individual-contributor and enterprise technical leader responsible for shaping architecture, driving hands-on execution, and elevating engineering practices across multiple teams. This role leads the design and delivery of secure, scalable, resilient and high-performing software, data and AI solutions while translating complex business needs into simple, extensible technical approaches.

The role combines deep expertise in modern application engineering, cloud platforms, data engineering and AI with broad organizational influence. The Principal Software Engineer partners with engineering, product, architecture, data science and business leaders; mentors engineers and technical leaders; and accelerates the responsible adoption of Generative AI, Agentic AI and intelligent automation.

Primary Responsibilities:

• AI-First Technical Leadership
  • Provide technical leadership for AI-powered products, copilots, agent-based systems and intelligent workflows, from architecture through production operation
  • Design practical solutions using Azure AI Foundry, GPT models, RAG architectures, vector search, knowledge graphs and agent orchestration frameworks where they create measurable value
  • Establish reusable engineering patterns for prompt design, model evaluation, grounding, observability, guardrails, security, privacy and Responsible AI
  • Champion the effective use of AI-assisted engineering workflows to improve software design, development, testing, documentation, operations and analytics
  • Evaluate emerging capabilities across Generative AI, multimodal AI, Agentic AI and LLMOps, and translate relevant advances into secure enterprise solutions
• Architecture and Solution Design
  • Lead the architecture, design and evolution of complex, business-critical systems across application, cloud, data and AI domains
  • Decompose complex business and technical problems into clear, maintainable and extensible architectures with well-defined boundaries and interfaces
  • Design distributed, cloud-native solutions using microservices, event-driven patterns, RESTful APIs, containers, serverless services and platform capabilities
  • Assess system interdependencies, scalability, reliability, performance, security, data quality and long-term maintainability when making design decisions
  • Define technical strategies and reference architectures that align product roadmaps with enterprise standards and modernization priorities
• Technical Execution and Innovation
  • Remain sufficiently hands-on to create prototypes, validate architectural choices, resolve critical technical challenges and guide implementation quality
  • Drive engineering solutions across NET/C#, React/TypeScript, Python and Scala, selecting technologies based on product and platform needs
  • Guide the design of data pipelines, ETL/ELT processes and analytical solutions using Azure Databricks, Apache Spark and modern lakehouse patterns
  • Lead performance engineering for high-volume systems, including database design, query optimization, throughput, latency and resource efficiency
  • Create reusable frameworks, accelerators and engineering assets, and contribute to patents, publications or other intellectual property where appropriate
• Engineering Excellence and Operational Readiness
  • Drive adoption of CI/CD, automated testing, Infrastructure as Code, containerization, observability and secure development lifecycle practices
  • Ensure production solutions meet expectations for availability, resilience, recoverability, supportability, compliance and data governance
  • Guide MLOps and LLMOps practices for versioning, deployment, evaluation, monitoring and lifecycle management of models and AI applications
  • Use architecture reviews, technical quality measures and operational feedback to identify systemic risks and improve engineering outcomes
  • Promote root-cause analysis and durable corrective actions for complex production and platform issues
• Mentorship and Organizational Influence
  • Mentor senior engineers, architects and emerging technical leaders through design reviews, pairing, coaching and technical forums
  • Influence engineering standards and roadmaps across multiple teams without relying on direct authority
  • Build alignment across product, engineering, architecture, data science, security and business stakeholders on key technical decisions
  • Communicate complex technical topics clearly to both technical and non-technical audiences, including trade-offs, risks and recommended decisions
  • Foster a culture of continuous learning, experimentation, inclusion, accountability and engineering excellence
• 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:

• Experience
  • Bachelor's or Master's degree in Computer Science, Software Engineering, Information Technology, Data Science, Artificial Intelligence or a related technical discipline, or equivalent practical experience
  • 10+ years of professional software engineering experience, including demonstrated leadership in the design and delivery of large-scale, complex systems
  • Proven experience operating as a senior technical leader across multiple teams, products or platforms
  • Hands-on experience delivering cloud-native, data-intensive or AI-enabled enterprise solutions into production
  • Demonstrated ability to influence technical strategy, resolve ambiguity and drive decisions across organizational boundaries
• Core Technical Expertise
  • Data engineering: Experience designing ETL/ELT pipelines and large-scale data processing solutions using Databricks, Spark, SQL and lakehouse or enterprise data platforms
  • DevOps and platform practices: Experience with Azure DevOps, GitHub Actions or Jenkins; Terraform or ARM/Bicep; Docker; Kubernetes; automated testing and observability
  • AI engineering: Experience building or integrating AI-powered applications using LLM APIs, prompt engineering, RAG, agentic patterns, model evaluation and production guardrails
  • Cloud engineering: Extensive hands-on experience with Microsoft Azure, including compute, integration, data, identity, container and serverless services
  • Application engineering: Deep expertise in multiple programming languages, with solid experience in NET/C#, React with JavaScript or TypeScript, Python and/or Scala
  • Architecture: Solid knowledge of distributed systems, microservices, event-driven architecture, API design, domain-driven design, design patterns and SOLID principles
  • Security and governance: Solid understanding of threat modeling, identity and access management, privacy, secure development lifecycle and enterprise compliance expectations
  • Databases: Solid proficiency in relational database design, SQL performance tuning and data modeling; working knowledge of NoSQL and vector data stores
• Leadership Capabilities:
  • Proven exceptional systems thinking, problem-solving and analytical judgment
  • Proven solid mentoring, facilitation, written communication and executive-level presentation skills
  • Proven curiosity and continuous-learning mindset across software, cloud, data and AI technologies
  • Proven ability to balance strategic architecture with pragmatic delivery and measurable outcomes
  • Proven ability to influence without authority, navigate disagreement and build durable technical consensus

Preferred Qualifications:

• Production experience with Azure AI Foundry, Azure OpenAI, Azure AI Search, MLflow, Azure Machine Learning or comparable AI platforms
• Experience with knowledge graphs, vector databases, multimodal AI, agent orchestration and decision-intelligence solutions
• Deep expertise in advanced Azure services such as Azure Kubernetes Service, Cosmos DB, Event Hubs, Azure Functions, Azure SQL, Data Factory or Synapse
• Experience with AWS or Google Cloud Platform in addition to Azure
• Experience designing real-time or high-traffic systems with demanding latency and throughput requirements
• Proven contributions to reusable engineering frameworks, open-source projects, patents, publications or industry technical communities

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.