UHG AI Architect

10 15 Years

Hybrid / Remote

We are seeking a highly experienced GenAI Architect to lead the design development and deployment of enterprise-scale Generative AI solutions. The ideal candidate will possess deep expertise in AI architecture multi-agent systems RAG pipelines cloud-native application development MLOps/LLMOps and healthcare-compliant AI systems.

The role requires strong technical leadership architecture governance stakeholder management and hands-on experience building production-grade AI platforms on Azure and AWS.

• Define end-to-end architecture for enterprise AI platforms and GenAI applications.
• Design scalable secure highly available distributed systems.
• Create architecture blueprints solution designs and technical roadmaps.
• Establish architecture standards governance frameworks and best practices.

• Design and implement autonomous AI agent ecosystems.
• Develop agent orchestration frameworks and agent collaboration workflows.
• Build planning reasoning memory and tool-calling capabilities.
• Evaluate and integrate agent frameworks such as LangGraph AutoGen CrewAI Semantic Kernel and custom orchestration solutions.

• Architect enterprise Retrieval-Augmented Generation (RAG) systems.
• Design document ingestion chunking embedding indexing retrieval reranking and response generation workflows.
• Implement vector database architectures using Pinecone Azure AI Search Weaviate Chroma FAISS or Elasticsearch.
• Optimize retrieval accuracy latency observability and cost.

• Design scalable Python microservices using FastAPI.
• Build APIs for LLM applications agents and AI workflows.
• Implement authentication authorization rate limiting and API security.
• Optimize backend performance for high-volume AI workloads.

• Define architecture for AI-powered web applications.
• Collaborate with frontend teams using React Angular or similar frameworks.
• Design conversational interfaces agent dashboards and AI workflow monitoring portals.
• Ensure responsive scalable and secure frontend solutions.

• Design relational and NoSQL database architectures.
• Optimize data models for AI workloads and enterprise-scale applications.
• Implement caching data partitioning and performance tuning strategies.
• Work with PostgreSQL SQL Server Cosmos DB MongoDB Redis and vector databases.

• Establish CI/CD pipelines for AI model deployment.
• Implement model monitoring observability evaluation and governance.
• Design prompt management versioning experimentation and deployment frameworks.
• Build automated workflows for model lifecycle management.

• Architect cloud-native AI platforms on Azure and AWS.
• Design secure scalable infrastructure using Infrastructure as Code.
• Utilize services such as:
  • Azure OpenAI
  • Azure AI Studio
  • Azure AI Search
  • Azure Kubernetes Service (AKS)
  • AWS Bedrock
  • AWS SageMaker
  • Amazon OpenSearch
  • Amazon EKS
• Implement disaster recovery security and compliance controls.

• Design AI solutions aligned with healthcare regulations.
• Ensure HIPAA-compliant data handling and governance.
• Implement secure PHI processing encryption auditing and access controls.
• Collaborate with healthcare stakeholders to build compliant AI products.

• Create and maintain:
  • Solution Architecture Documents (SAD)
  • High-Level Designs (HLD)
  • Low-Level Designs (LLD)
  • Architecture Decision Records (ADR)
  • Technical Standards Documents
  • Risk and Compliance Assessments

• Provide technical leadership across engineering teams.
• Mentor architects engineers and AI practitioners.
• Present architecture strategies to executive leadership.
• Drive technical discussions with business product security and compliance stakeholders.
• Lead architecture reviews and governance boards.