Principal Architect - Remote

UnitedHealth Group•Hartford, CT

3d•$112,700 - $193,200•Remote

About The Position

As part of the Optum Health Financial Tech team, the Principal Architect defines and owns end-to-end architecture for AI-enabled and Generative AI solutions that meet business outcomes and enterprise requirements for scalability, security, and compliance. The role designs reference architectures for LLM-based systems, evaluates AI platforms and foundation models, and integrates AI capabilities into existing microservices and event-driven data platforms. It serves as a technical authority across cross-functional engineering teams, advancing AI innovation and Responsible AI while delivering scalable, high-performance solutions. The position is remote from anywhere within the U.S. Employees hired in the Minneapolis or Washington, D.C. area must work in the office at least four days per week. Remote employees must follow UnitedHealth Group’s Telecommuter Policy.

Requirements

At least 8 years of experience translating complex business requirements into scalable, secure, high-performance software architectures.
At least 6 years of software engineering experience, including at least 3 years in a Technical Architect or Solution Architect role.
At least 6 years of experience working with Java, Spring Boot, microservices, Kafka, APIs, Azure Cloud, Databricks, and relational/non-relational databases such as SQLMI.
At least 4 years of experience with microservices, APIs, event-driven systems, and containerized deployments.
At least 4 years of experience leading design reviews, defining technical standards, and providing oversight across cross-functional teams.
At least 2 years of experience with Azure cloud services, including integrating Azure OpenAI into enterprise solutions.
At least 1 year of experience designing and implementing LLM-based solutions, including RAG, prompt orchestration, and agent-driven architectures.

Nice To Haves

Bachelor’s degree in Computer Science, Engineering, or a related technical field.
Hands-on experience with vector databases, model gateways, and fine-tuning foundation models.
Experience in healthcare or financial technology domains.
Experience using AI-assisted developer productivity tools such as GitHub Copilot and establishing standards for AI-generated code review and security scanning.

Responsibilities

Define and own end-to-end architecture for AI-enabled and Generative AI solutions aligned with business outcomes, scalability, security, and enterprise compliance.
Design reference architectures for LLM-based systems, including prompt orchestration, RAG, agent frameworks, and model integration patterns.
Evaluate and recommend AI platforms, foundation models, and tooling, such as Azure OpenAI, vector databases, and 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 enterprise integration.
Architect AI-driven workflows that integrate with microservices, data platforms, APIs, and event-driven systems such as Kafka and Databricks.
Embed Responsible AI principles—including privacy, fairness, explainability, model risk management, prompt guardrails, and auditability—into solution designs.
Provide hands-on architectural guidance, technical oversight, and performance tuning for complex AI implementations across onshore and offshore teams.
Promote AI-assisted development practices using enterprise tools to improve developer productivity, code quality, and test coverage.