Senior Java Agentic AI Engineer (Only W2 & F2F interview local to GA )

Job Summary

We are seeking an experienced Senior Java Agentic AI Engineer with strong expertise in Java 21+, Spring Boot, and AI-powered application development. The ideal candidate will design, develop, and deploy production-grade APIs and intelligent AI agent solutions using modern Java frameworks and Large Language Models (LLMs).

The candidate should have hands-on experience with agent orchestration, prompt engineering, Retrieval-Augmented Generation (RAG), LLM evaluation, observability, and cloud-based AI deployments. This role requires strong software engineering fundamentals combined with practical experience building scalable, secure, and cost-efficient AI applications.

Key Responsibilities

• Design, develop, and maintain scalable backend services and production APIs using Java 21+ and Spring Boot 3.x.

• Build and integrate AI agents using Spring AI or LangChain4j within enterprise Java applications.

• Develop effective prompt templates, system instructions, role definitions, and constraints for LLM-powered applications.

• Implement agentic workflows involving tool calling, memory management, planning, retries, and guardrails.

• Design and develop evaluation frameworks to measure LLM response quality, accuracy, reliability, and performance.

• Implement LLM observability and monitoring using tools such as Langfuse, Arize, Weights & Biases, or Datadog.

• Monitor and optimize model traces, response latency, token consumption, cost, and failure rates.

• Apply RAG techniques, including document chunking, embeddings, vector databases, and retrieval optimization.

• Optimize LLM performance and operational costs through caching, batching, model routing, and prompt/token optimization.

• Evaluate and select AI models based on response quality, latency, cost, and risk.

• Deploy and manage scalable, secure AI services across AWS, Azure, or Google Cloud Platform environments.

• Collaborate with engineering teams to implement AI-driven software development practices and production-ready solutions.

Required Skills & Qualifications

• Strong hands-on experience with Java 21+ and Spring Boot 3.x.

• Proficiency in Spring Web, Spring Data, and Spring Security.

• Experience building production-grade REST APIs and backend microservices.

• Hands-on experience with Spring AI or LangChain4j.

• Strong understanding of Generative AI, LLMs, and agentic AI architecture.

• Practical experience in prompt engineering and prompt optimization.

• Experience with AI agent orchestration, tool calling, memory, planning, retries, and guardrails.

• Knowledge of RAG architecture, embeddings, vector databases, and retrieval tuning.

• Experience designing and implementing LLM evaluations and quality benchmarks.

• Familiarity with LLM observability platforms such as Langfuse, Arize, Weights & Biases, or Datadog.

• Experience with LLM performance monitoring, cost optimization, and model selection.

• Cloud deployment experience with AWS, Azure, or Google Cloud Platform.

• Familiarity with AI coding assistants such as GitHub Copilot or Amazon Q.

Preferred Qualifications

• Experience with CLI-based AI coding assistants such as Copilot CLI or Claude Code.

• Understanding of AI-driven software development and Spec-Driven Development (SDD).

• Familiarity with Model Context Protocol (MCP) and OpenAPI tool schemas.

• Experience integrating interoperable tools and services into AI agent workflows.

• Strong understanding of secure, scalable, and maintainable enterprise application development.