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Business Consulting, Coaching, Financial Advisory

Generative AI Engineer

Three Rivers, Michigan, United StatesHybridFull TimePosted 2 months ago

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Role summary

We are seeking a Generative AI Engineer with 6+ years of experience to join our hybrid team in Basking Ridge, NJ. This role focuses on architecting and deploying stateful agentic systems using LangGraph and LangChain, with a strong emphasis on Python backend development using FastAPI and Pydantic for high-concurrency AI workloads. You will optimize RAG pipelines with Elasticsearch and build robust cloud infrastructure on GCP, integrating with Vertex AI. Experience with AI observability tools like Galileo and frontend integration using React.js is also crucial for this position.

Role: Generative AI Engineer
Location: Basking Ridge NJ
Experience: 6+ years
Work Mode: Hybrid (3 days WFO)
Core Responsibilities

  • Architect Agentic Systems: Design and deploy stateful agents using LangGraph and LangChain, focusing on long-running workflows with unified PostgreSQL checkpointers for persistent state management
  • Develop High-Performance APIs: Build robust backends using Python (Asyncio), FastAPI, and Pydantic to handle high-concurrency AI workloads
  • Optimize Retrieval (RAG): Implement advanced RAG pipelines using Elasticsearch (Vector Search), cross-encoders for re-ranking, and custom embedding services
  • Infrastructure & Deployment: Deploy containerized AI services on Google Cloud Platform (GCP), integrating seamlessly with Google Vertex AI
  • Engineering Excellence: Adapt and contribute to internal SDKs that extend open-source frameworks to provide enterprise-grade observability, model routing, and state persistence
  • Frontend Integration: Build intuitive UIs in React.js to allow users to interact with complex agentic outputs and FastAPI backends

Technical Requirements
Python & Backend Excellence

  • Expertise in Object-Oriented Programming (OOP) and asynchronous patterns (async/await)
  • Deep experience with FastAPI and data validation using Pydantic models

GenAI & Agentic Frameworks

  • LangChain/LangGraph: Proven track record of building stateful agents
  • Protocol Knowledge: Familiarity with Agent-to-Agent (A2A) protocols for multi-agent coordination and Model Context Protocol (MCP) for building dedicated tool servers
  • Observability: Experience using frameworks like Galileo for AI evaluation and monitoring

Data & Search Layer

  • PostgreSQL: Proficiency in managing task coordination, state storage, and unified connection pooling
  • Elasticsearch: Practical knowledge of document indexing, Vector DBs, and retrieval strategies (Similarity search, Hybrid search)

Cloud & DevOps

  • Hands-on experience with GCP, specifically deploying containerized services (Cloud Run/GKE)
  • Integration experience with Vertex AI model ecosystems
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