Principal Architect - Remote

UnitedHealth Group•Eden Prairie, MN

8d•$112,700 - $193,200•Remote

About The Position

Optum Insight is improving the flow of health data and information to create a more connected system. We remove friction and drive alignment between care providers and payers, and ultimately consumers. Our deep expertise in the industry and innovative technology empower us to help organizations reduce costs while improving risk management, quality and revenue growth. Ready to help us deliver results that improve lives? Join us to start Caring. Connecting. Growing together. 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.

Requirements

Bachelor’s degree in Computer Science, Engineering, or a related technical field
10+ years of experience with complex business requirements into scalable, secure, and high performance architectures
8+ years of experience in software engineering with at least 3+ years in a Technical Architect or Solution Architect role
8+ years of experience with Java, Springboot, MicroServices, Kafka, API, Azure cloud, Databricks, SQLMI (or any DB)
5+ years of experience with microservices, APIs, event driven systems, and containerized deployments
5+ years of experience with lead design reviews, define standards, and provide technical oversight across cross functional teams
3+ years of experience Azure cloud services with experience integrating Azure OpenAI into enterprise solutions
2+ years of experience designing and implementing LLM based solutions, including RAG, prompt orchestration, and agent driven architectures

Nice To Haves

Master’s degree
Proven knowledge of responsible AI principles, data privacy, security controls, and governance frameworks
Proven solid stakeholder management skills with the ability to work closely with Product, Business, Engineering, Data, and Security teams
Demonstrated experience architecting enterprise scale solutions in cloud environments (Azure preferred)
Practical experience delivering AI enabled or GenAI solutions in production environments

Responsibilities

Define and own end to end architecture for AI enabled and Generative AI solutions aligned with business outcomes, scalability, security, and compliance
Design reference architectures for LLM based systems, including prompt orchestration, RAG (Retrieval Augmented Generation), agent frameworks, and model integration patterns
Evaluate and recommend AI platforms, foundation models, and tooling (e.g., Azure OpenAI, vector databases, model gateways) based on use case fit and enterprise standards
Translate business and product requirements into scalable AI solution designs covering data ingestion, embeddings, model inference, orchestration, and integration with enterprise systems
Architect AI driven workflows that integrate with existing microservices, data platforms, APIs, and event driven systems
Provide hands on architectural guidance for complex AI implementations, including performance tuning and cost optimization
Embed Responsible AI principles including privacy, fairness, explainability, model risk management, and auditability into solution designs
Define guardrails for prompt management, data access, content filtering, and human in the loop controls
Ensure AI solutions comply with enterprise security, regulatory, and data governance standards.
Act as the technical authority for AI initiatives, guiding teams through architectural decisions and design trade offs
Design scalable cloud native and hybrid AI platforms supporting training, fine tuning, inference, and monitoring
Ensure high availability, resiliency, and observability for AI systems in production
Promote AI assisted development practices using tools such as GitHub Copilot to improve developer productivity, code quality, and test coverage
Establish standards for AI generated code review, validation, and security scanning
Act as a bridge between business stakeholders and technical teams to align AI capabilities with real business value
Support onshore/offshore teams with architectural direction and AI adoption guidance
Drive modernization initiatives leveraging GenAI for automation, insights, and improved user experience
Continuously refine AI architectures based on evolving business needs, usage patterns, and model performance