AI Architect - Enterprise AI & Generative AI Platforms - Multiple locations; Remote

UnitedHealth Group•Minneapolis, MN

23h•$112,700 - $193,200•Remote

About The Position

We are seeking a highly skilled and hands-on AI Architect to lead the design, development, and implementation of enterprise-scale AI and Generative AI solutions. This role requires deep technical expertise across AI/ML architectures, cloud-native platforms, data engineering, APIs, integration patterns, and modern software engineering practices. The ideal candidate combines strategic architecture leadership with strong hands-on engineering capabilities and can guide teams from ideation through production deployment of AI-driven solutions. The AI Architect will collaborate with product, engineering, security, platform, and business stakeholders to build scalable, secure, compliant, and responsible AI ecosystems. 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 or Master’s degree in Computer Science, Engineering, AI, Data Science, or related field
10+ years of software engineering/architecture experience
Hands-on experience with AI/ML or Generative AI implementation
Solid expertise in Python
Solid expertise in APIs & microservices
Solid expertise in Cloud-native architectures
Solid expertise in Kubernetes & containers
Solid expertise in AI/ML frameworks
Experience deploying enterprise solutions in production environments

Nice To Haves

Experience in healthcare, finance, or regulated industries
Familiarity with FHIR, HL7, or healthcare interoperability standards
Experience with enterprise API governance and streaming platforms
Knowledge of responsible AI frameworks and AI security controls
AI/Cloud certifications
Solid communication and stakeholder management
Ability to influence executive and engineering leadership
Solid problem-solving and architecture decision-making skills
Ability to balance strategic thinking with hands-on execution

Responsibilities

Design enterprise-grade AI/ML and Generative AI architectures aligned with business and technology strategies
Define scalable patterns for LLM integration, RAG (Retrieval-Augmented Generation), Agentic AI workflows, AI orchestration frameworks, Vector databases, AI gateways, and Model serving and inference
Architect multi-cloud AI solutions across Azure, AWS, and GCP
Define AI platform standards, reusable components, and reference architectures
Build production-ready AI services and APIs using Python, Java, or Node.js.
Develop and optimize Prompt engineering frameworks, AI agents, Semantic search pipelines, Embedding workflows, and Fine-tuning pipelines
Implement integrations with enterprise systems using APIs, event-driven architectures, and streaming technologies
Work directly with engineering teams on coding, troubleshooting, performance tuning, and deployment automation
Evaluate and implement enterprise LLM solutions including OpenAI, Anthropic, Gemini, and open-source models
Design secure and compliant GenAI architectures with guardrails, governance, and observability
Implement RAG pipelines, Vector search, Knowledge grounding, AI evaluation frameworks, and Hallucination mitigation strategies
Establish responsible AI practices including explainability, privacy, and bias mitigation
Design AI infrastructure on Azure OpenAI, AWS Bedrock, Vertex AI, Kubernetes, and container platforms
Build CI/CD pipelines for ML and AI workloads
Implement MLOps and LLMOps practices for model lifecycle management
Drive infrastructure automation using Terraform, Helm, GitHub Actions, or Azure DevOps
Collaborate with data engineering teams to build scalable AI data pipelines
Design event-driven and streaming architectures using Kafka and modern integration frameworks
Ensure interoperability and API-first design principles across platforms
Define enterprise AI standards, policies, and architecture governance
Mentor engineers and architects on AI best practices
Conduct architecture reviews and technology evaluations
Partner with security and compliance teams to ensure adherence to enterprise standards