Generative AI Engineer
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
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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