Strictly Local Candidates - Detroit/ MI
We are seeking a highly skilled Agentic AI Architect to lead the design and development of sophisticated AI agent systems using Google Cloud Platform's Vertex AI suite. This hands-on role requires deep expertise in building autonomous AI systems that can reason, plan, and execute complex tasks using large language models and advanced orchestration frameworks.
Key Responsibilities
Design and implement agentic AI architectures using Google Vertex AI models (Gemini, PaLM, Codey)
Develop and deploy AI agents using LangChain and Model Context Protocol (MCP) architectures
Build scalable, production-ready AI systems leveraging GCP services including Vertex AI Pipelines, Matching Engine, and AI Platform
Implement multi-agent systems with complex reasoning, planning, and tool-use capabilities
Design and optimize vector databases and embedding systems for retrieval-augmented generation (RAG)
Integrate agents with external APIs, databases, and enterprise systems
Establish MLOps practices for agent deployment, monitoring, and continuous improvement
Required Technical Skills
Core AI & ML:
Extensive experience with Google Vertex AI suite (Gemini Pro/Ultra, PaLM 2, Codey, Imagen)
Deep understanding of agentic AI patterns: ReAct, Chain-of-Thought, Tree of Thoughts, and multi-agent workflows
Proficiency with LangChain, LangGraph, and agent orchestration frameworks
Experience with Model Context Protocol (MCP) for agent-to-agent communication
Knowledge of prompt engineering, fine-tuning, and model optimization techniques
Google Cloud Platform:
Vertex AI Workbench, Pipelines, and Model Registry
Cloud Functions, Cloud Run, and App Engine for serverless deployments
BigQuery for data processing and analytics
Cloud Storage, Firestore, and Cloud SQL for data management
Pub/Sub for event-driven architectures
Cloud Logging, Monitoring, and Error Reporting
Programming & Development:
Advanced Python programming (5+ years)
Experience with FastAPI, Flask, or Django for API development
Containerization with Docker and Kubernetes (GKE)
Infrastructure as Code (Terraform, Cloud Deployment Manager)
Version control with Git and CI/CD pipelines (Cloud Build, GitHub Actions)
Data & Vector Systems:
Vector databases (Vertex AI Matching Engine, Pinecone, Weaviate, or Chroma)
Embedding models and similarity search optimization
Knowledge graph construction and reasoning
Structured and unstructured data processing
Preferred Qualifications
Experience with additional agent frameworks (AutoGen, CrewAI, Semantic Kernel)
Knowledge of graph databases (Neo4j, Amazon Neptune)
Familiarity with other cloud platforms (AWS Bedrock, Azure OpenAI)
Understanding of function calling, tool use, and external API integration
Experience with streaming and real-time AI applications
Background in distributed systems and microservices architecture
Knowledge of AI safety, alignment, and responsible AI practices
Experience Requirements
10+ years in software engineering with 3+ years focused on AI/ML systems
2+ years hands-on experience with production LLM applications
Demonstrated experience building and deploying agentic AI systems
Track record of architecting scalable cloud-native applications
Experience leading technical teams and mentoring junior developers
Education
Bachelor's or Master's degree in Computer Science, AI/ML, or related technical field Preferred
Relevant certifications (Google Cloud Professional ML Engineer, AI/ML specializations) preferred
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