Technical AI Architect

Technical AI Architect at Apexon Technical AI Architect at Apexon in Auburn Hills, Michigan Posted in 1 day ago.

Type:

full-time

Job Description:

Technical Architect - AI Auburn Hills, MI (Onsite) Full-Time (FTE) Key Responsibilities Platform Architecture & Governance Design 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

Engineering Architect 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 Architecture Lead 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 Integration Architect 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 Management Collaborate 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 Skills

AI / LLM

Frameworks LangGraph, LangChain, MCP Amazon Bedrock, SageMaker, Amazon Q Bedrock Agents & Knowledge Bases Prompt Engineering, Fine-Tuning, Evaluation Frameworks Multi-Agent AI Systems & RAG Architectures AWS Cloud & DevOps AWS EKS, Lambda, ECS Fargate, API Gateway Terraform, AWS CDK, CloudFormation CI/CD using CodePipeline, CodeBuild, GitHub Actions Docker & Kubernetes (EKS) Programming Advanced Python with

FastAPI Java Integration Experience Data & Vector Databases OpenSearch, Pinecone, Weaviate, Chroma Embedding Models, Hybrid Search, Reranking Graph DBs:

Neptune / Neo4j Salesforce Integration Agentforce, Einstein, Data Cloud, Service Cloud Apex, Flow, Platform Events, REST APIs Security & Governance IAM, KMS, VPC, GuardDuty, Macie, Security Hub DLP, Audit Logging, AI Governance Frameworks Experience Required 20+ years in Software Engineering 5+ years in AI/ML systems 3+ years building production-grade LLM / Agentic AI applications Strong AWS enterprise architecture experience Leadership experience managing technical teams and enterprise stakeholders Preferred Certifications AWS Certified Solutions Architect - Professional AWS Certified Machine Learning - Specialty Salesforce AI Associate / AI Specialist / Application Architect Certifications