Generative AI Engineer

Role: Generative AI Engineer Location: Basking Ridge NJExperience: 6+ years Work Mode: Hybrid (3 days WFO)Core ResponsibilitiesArchitect Agentic Systems: Design and deploy stateful agents using LangGraph and LangChain, focusing on long-running workflows with unified PostgreSQL checkpointers for persistent state managementDevelop High-Performance APIs: Build robust backends using Python (Asyncio), FastAPI, and Pydantic to handle high-concurrency AI workloadsOptimize Retrieval (RAG): Implement advanced RAG pipelines using Elasticsearch (Vector Search), cross-encoders for re-ranking, and custom embedding servicesInfrastructure & Deployment: Deploy containerized AI services on Google Cloud Platform (GCP), integrating seamlessly with Google Vertex AIEngineering Excellence: Adapt and contribute to internal SDKs that extend open-source frameworks to provide enterprise-grade observability, model routing, and state persistenceFrontend Integration: Build intuitive UIs in React.js to allow users to interact with complex agentic outputs and FastAPI backendsTechnical RequirementsPython & Backend ExcellenceExpertise in Object-Oriented Programming (OOP) and asynchronous patterns (async/await)Deep experience with FastAPI and data validation using Pydantic modelsGenAI & Agentic FrameworksLangChain/LangGraph: Proven track record of building stateful agentsProtocol Knowledge: Familiarity with Agent-to-Agent (A2A) protocols for multi-agent coordination and Model Context Protocol (MCP) for building dedicated tool serversObservability: Experience using frameworks like Galileo for AI evaluation and monitoringData & Search LayerPostgreSQL: Proficiency in managing task coordination, state storage, and unified connection poolingElasticsearch: Practical knowledge of document indexing, Vector DBs, and retrieval strategies (Similarity search, Hybrid search)Cloud & DevOpsHands-on experience with GCP, specifically deploying containerized services (Cloud Run/GKE)Integration experience with Vertex AI model ecosystems