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Lead Agentic AI & Java Integration Engineer

India, Bangalore · Job Posted May 15, 2026
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Job Description

We are currently seeking a Lead Agentic AI & Java Integration Engineer to join our team in Bangalore, Karnātaka (IN-KA), India (IN). Job Duties: Role Overview: We are looking for a Lead Agentic AI Engineer to drive the evolution of our enterprise applications by embedding advanced, multi-step LLM reasoning. This is a highly strategic, hands-on role where you will build intelligent AI agents and integrate them deeply into our massive-scale Java/Spring Boot ecosystem. You will not only build complex RAG pipelines and autonomous agents but also establish the enterprise guardrails, evaluation metrics, and engineering standards necessary to safely deploy AI into highly regulated business workflows (such as intelligent financial/FX insights).

Job Responsibility

  • Agentic System Orchestration: Design and orchestrate sophisticated AI agents using LangChain and LangGraph. Manage complex control flows, tool calling, memory management, and multi-step reasoning workflows
  • Enterprise RAG & Search: Architect robust GenAI patterns, including Retrieval-Augmented Generation (RAG), semantic search, vector database integration, and end-to-end embeddings lifecycle management
  • Java/Spring Boot Integration: Seamlessly integrate GenAI capabilities and agent workflows into large-scale, distributed, event-driven enterprise applications built on Java, Spring Boot, and microservices architectures
  • AI Guardrails & Security: Engineer robust enterprise guardrails encompassing prompt injection defenses, data privacy filters, safety constraints, explainability, and Human-in-the-Loop (HITL) approval flows
  • Evaluation & Operationalization: Define and automate rigorous GenAI evaluation pipelines using frameworks like DeepEval. Continuously monitor models for accuracy, contextual relevance, hallucinations, conceptual drift, latency, and operational cost
  • Technical Leadership & Mentorship: Serve as the domain expert for GenAI engineering standards. Mentor development teams on architectural decision-making, specifically determining when to utilize agent-based systems versus conventional deterministic services

Requirements

  • 8+ years of progressive software engineering experience, with a core foundation in enterprise Java and Spring Boot
  • Deep, hands-on expertise in Agentic AI frameworks (LangChain, LangGraph) and prompt engineering (structured outputs, function/tool calling)
  • Proven experience building and scaling RAG pipelines and working intimately with Vector Databases
  • Extensive experience implementing AI evaluation frameworks (e.g., DeepEval) and LLM observability metrics
  • Strong background in distributed systems, event-driven architectures, and building resilient API ecosystems
  • Demonstrated ability to translate highly ambiguous, complex business problems into secure, reliable, and compliant production-ready systems
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