AI/Machine Learning Architect

Brooksource

Fortune 50 Health Insurance Client

Remote

About the Project

Our client is scaling an enterprise AI search and conversational platform supporting benefits and care navigation across multiple lines of business. The platform is evolving toward an agent-driven architecture that integrates enterprise knowledge bases, LLMs, and orchestration layers to deliver trustworthy, contextual responses to members.

This role will define the architectural foundation and governance model for agentic AI, RAG systems, and AI integration across secure digital platforms.

Role Summary

The AI/ML Architect will lead the design of the agent processing and AI orchestration layer that powers intelligent search and conversational experiences. This role focuses on architecture, standards, governance, observability, and enterprise integration patterns — ensuring AI systems are scalable, secure, and production-ready.

This architect will also mentor engineers, establish best practices, and help build a repeatable playbook for enterprise AI delivery.

Key Responsibilities

AI & Agent Architecture

• Define architecture for agentic AI and agent processing/orchestration layers
• Design end-to-end RAG and LLM solution architectures across enterprise platforms
• Architect integration between knowledge bases and enterprise AI gateways
• Define patterns for contextual AI responses across channels

MCP & Agent Frameworks

• Lead design and implementation standards for Model Context Protocol (MCP) servers
• Define how MCP servers integrate with agent processing layers
• Establish reusable patterns for tool use, context injection, and agent workflows
• Guide MCP server build and deployment approaches

Governance & Standards

• Establish AI architecture standards and guardrails
• Define governance models for model usage, knowledge sources, and prompt frameworks
• Ensure compliance with enterprise security and data governance requirements
• Create architectural review and approval patterns

Observability & Reliability

• Define AI observability and monitoring strategies
• Implement tooling and standards for tracing and evaluation (ex: Langfuse or similar)
• Establish performance, quality, and safety monitoring frameworks
• Define evaluation methodologies for AI responses and agent behavior

Platform & Enterprise Integration

• Serve as architectural liaison between enterprise AI platform teams and application teams
• Define integration patterns across digital, mobile, and conversational channels
• Align AI architecture with enterprise data pipelines and gateways
• Guide onboarding of new AI components and vendors

Mentorship & Enablement

• Mentor AI/ML engineers and platform teams
• Develop architectural playbooks and reference implementations
• Lead knowledge sessions and internal workshops
• Contribute to a long-term “AI excellence” capability vision

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, AI, or related field
• 7+ years in AI/ML or advanced software architecture roles
• Proven experience architecting LLM, RAG, and agent-based AI systems
• Strong knowledge of:
  • Agent architectures
  • MCP servers and protocols
  • Knowledge base integration
  • AI orchestration layers
• Deep experience with cloud AI architecture (Azure or AWS)
• Experience designing production AI governance and monitoring frameworks
• Strong background in APIs, microservices, and distributed systems
• Excellent communication and technical leadership skills

Preferred Qualifications

• Experience with enterprise AI gateways
• Experience with AI observability tools (Langfuse or similar)
• Healthcare or regulated industry experience
• Experience scaling AI platforms across multiple business domains
• Agile enterprise delivery experience