Technical Architect – AI

Technical Architect – AI

Location:

Auburn Hills, MI (Day 1 Onsite)

We are seeking an experienced AI Technical Architect to lead the design, governance, and implementation of enterprise-scale AI platforms and agentic AI solutions. The ideal candidate will have deep expertise in AI/LLM architecture, AWS cloud services, MLOps, enterprise integrations, and security governance.

• Design enterprise AI platform architecture including LLM API gateways, GPU/compute allocation, sandbox provisioning, model registry, and security automation.
• Define infrastructure standards, API gateway patterns, and reusable reference architectures for AI delivery teams and partner integrations.
• Establish governance controls for token metering, rate limiting, audit logging, DLP validation, SAST/DAST, dependency scanning, and model review processes within CI/CD pipelines.
• Ensure AI workloads align with NIST AI RMF, AWS Well-Architected Framework, ML Lens, and enterprise compliance standards.

• Architect multi-agent AI systems using Lang Graph, Lang Chain, and MCP (Model Context Protocol).
• Design orchestration patterns including ReAct, Chain-of-Thought, Tree-of-Thoughts, and agent-to-agent collaboration.
• Build and optimize RAG architectures, semantic search frameworks, embedding pipelines, and enterprise knowledge retrieval systems.
• Establish MLOps and Agent Ops practices for deployment, monitoring, evaluation, and continuous optimization of AI systems.

• Architect AI solutions using Amazon Bedrock, Sage Maker, Amazon Q, Bedrock Agents, and Bedrock Knowledge Bases.
• Define scalable cloud-native patterns leveraging EKS, Lambda, ECS Fargate, API Gateway, Event Bridge, SNS/SQS, Kinesis, S3, DynamoDB, Aurora, Redshift, Athena, Open Search, and Kendra.
• Develop infrastructure automation using AWS CDK, Cloud Formation, and Terraform for secure multi-tenant sandbox environments.
• Implement observability, cost governance, and Fin Ops using Cloud Watch, AWS Budgets, Cost Explorer, and chargeback models.

• Design integrations with Salesforce Agentforce, Einstein, Data Cloud, and Service Cloud.
• Define integration patterns using Apex, Flow, Platform Events, and AWS-hosted AI services.
• Establish governance for enterprise SaaS AI licensing, usage optimization, and cross-platform identity management.

• Collaborate with AI leadership, security, compliance, procurement, and engineering teams to drive AI platform adoption.
• Create enterprise architecture documentation, decision records, and governance artifacts.
• Lead architecture reviews, technical due diligence, and mentor engineering teams across multiple delivery towers.

• Strong experience in enterprise AI/LLM architecture and Agentic AI frameworks.
• Hands-on expertise with Lang Chain, Lang Graph, MCP, RAG, and semantic search solutions.
• Deep AWS cloud architecture experience including Bedrock, Sage Maker, EKS, Lambda, and serverless services.
• Experience with MLOps, Agent Ops, CI/CD security automation, and observability.
• Knowledge of AI governance, security, and compliance frameworks.
• Experience integrating AI platforms with Salesforce ecosystems.
• Strong stakeholder management and enterprise architecture documentation skills.