Technical AI Architect

Technical Architect – AIAuburn Hills, MI (Onsite)Full-Time (FTE)Key ResponsibilitiesPlatform Architecture & GovernanceDesign enterprise AI platform architecture including LLM API gateways, GPU/compute allocation, sandbox environments, model registry, and security automation.Define infrastructure standards, API gateway patterns, and reusable reference architectures.Establish governance for token metering, rate limiting, audit logging, DLP, SAST/DAST, dependency scanning, and model reviews within CI/CD.Ensure AI workloads align with NIST AI RMF, AWS Well-Architected Framework, and enterprise compliance standards.Agentic AI & LLM EngineeringArchitect multi-agent AI systems using LangGraph, LangChain, and MCP.Design orchestration patterns including ReAct, Chain-of-Thought, Tree-of-Thoughts, and agent collaboration frameworks.Build scalable RAG architectures, semantic search, and embedding strategies across enterprise datasets.Define MLOps and AgentOps best practices for deployment, monitoring, evaluation, and optimization.AWS-Native ArchitectureLead architecture on Amazon Bedrock, SageMaker, Amazon Q, Bedrock Agents, and Knowledge Bases.Build scalable cloud-native solutions using EKS, Lambda, ECS Fargate, API Gateway, EventBridge, SNS/SQS, Kinesis, S3, DynamoDB, Aurora, Redshift, Athena, OpenSearch, and Kendra.Develop IaC solutions using Terraform, CloudFormation, and AWS CDK.Implement observability and FinOps using CloudWatch, AWS Budgets, and Cost Explorer.Salesforce & SaaS AI IntegrationArchitect integrations with Salesforce Agentforce, Einstein, Data Cloud, and Service Cloud.Define secure identity, authorization, and API integration patterns across AWS, Salesforce, and external systems.Manage governance of enterprise AI SaaS licensing and usage optimization.Leadership & Stakeholder ManagementCollaborate with engineering, security, compliance, procurement, and executive stakeholders.Create enterprise-grade architecture documentation and operating models.Mentor engineering teams and conduct architecture reviews and technical due diligence.Mandatory SkillsAI / LLM FrameworksLangGraph, LangChain, MCPAmazon Bedrock, SageMaker, Amazon QBedrock Agents & Knowledge BasesPrompt Engineering, Fine-Tuning, Evaluation FrameworksMulti-Agent AI Systems & RAG ArchitecturesAWS Cloud & DevOpsAWS EKS, Lambda, ECS Fargate, API GatewayTerraform, AWS CDK, CloudFormationCI/CD using CodePipeline, CodeBuild, GitHub ActionsDocker & Kubernetes (EKS)ProgrammingAdvanced Python with FastAPIJava Integration ExperienceData & Vector DatabasesOpenSearch, Pinecone, Weaviate, ChromaEmbedding Models, Hybrid Search, RerankingGraph DBs: Neptune / Neo4jSalesforce IntegrationAgentforce, Einstein, Data Cloud, Service CloudApex, Flow, Platform Events, REST APIsSecurity & GovernanceIAM, KMS, VPC, GuardDuty, Macie, Security HubDLP, Audit Logging, AI Governance FrameworksExperience Required20+ years in Software Engineering5+ years in AI/ML systems3+ years building production-grade LLM / Agentic AI applicationsStrong AWS enterprise architecture experienceLeadership experience managing technical teams and enterprise stakeholdersPreferred CertificationsAWS Certified Solutions Architect – ProfessionalAWS Certified Machine Learning – SpecialtySalesforce AI Associate / AI Specialist / Application Architect Certifications