Java Full Stack Developer (React + Agentic AI)

Happiest Minds Technologies; Pune District, Bengaluru, Dadri; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Happiest Minds Technologies in Pune is seeking engineers to design and build agentic AI systems that reason, plan, and execute complex workflows using Large Language Models. You will develop AI-powered services with OpenAI/Azure OpenAI and orchestrate agents with Lang Chain, Llama Index, and vector databases.

You will also implement scalable Java backends using Spring Boot and Netflix DGS, plus Python microservices with FastAPI to expose agent capabilities.

Qualifications

• Experience designing scalable AI-powered frontend and backend services.
• Proficient in building LLM-driven workflows and agent orchestration.
• Familiarity with cloud services and enterprise integrations.

Responsibilities

• Design and develop Agentic AI systems capable of reasoning and executing complex workflows with LLMs.
• Build AI-powered services using LLM APIs such as OpenAI and Azure OpenAI.
• Develop and orchestrate AI agents using Lang Chain, Lang Graph, and Llama Index.
• Create multi-agent systems with task decomposition and tool usage.
• Integrate vector databases for semantic search and retrieval.
• Build scalable backend services in Java Spring Boot for enterprise integrations.
• Write Python services for LLM orchestration and prompt engineering.
• Develop AI microservices with FastAPI exposing agent capabilities.
• Integrate AI agents with enterprise systems via REST APIs and event streams.
• Design tool integrations for AI agents to interact with internal services.
• Implement memory architectures and observability to monitor LLM performance and behavior.

Skills

React

TypeScript

Python

Java

Frontend development

WebSocket

Tools

Lang Chain

Lang Graph

Llama Index

PgVector

Pinecone

Weaviate

Milvus

Spring Boot

Netflix DGS

Azure OpenAI

Azure Functions

AKS

REST APIs

Job description

Key Responsibilities-

Design and develop Agentic AI systems capable of reasoning, planning, and executing complex workflows using Large Language Models.

Build AI-powered services using LLM APIs such as OpenAI, Azure OpenAI Service, or other foundation model providers.

Develop and orchestrate AI agents using frameworks such as Lang Chain, Lang Graph, and Llama Index.

Design and implement multi-agent systems, including agent collaboration, task decomposition, and tool usage.

Build Retrieval-Augmented Generation (RAG) pipelines integrating enterprise knowledge sources.

Integrate vector databases such as PgVector, Pinecone, Weaviate, or Milvus to enable semantic search and knowledge retrieval.

Build scalable backend services using Java (Spring Boot / Netflix DGS) for enterprise integrations and high-throughput APIs.

Write Python services using Object-Oriented design principles to support LLM orchestration, prompt engineering, and agent execution.

Develop AI microservices using FastAPI to expose agent capabilities and LLM-powered workflows.

Integrate AI agents with enterprise systems via REST APIs, event streams, and databases.

Design and implement tool integrations enabling AI agents to interact with internal services, APIs, and automation workflows.

Implement memory architectures for AI agents including short‑term memory, long‑term knowledge retrieval, and context management.

Design observability, monitoring, and evaluation frameworks to measure LLM performance, agent behaviour, hallucination rates, and task success.

Optimize prompt engineering, model selection, token usage, latency, and cost efficiency.

Build guardrails and safety mechanisms for reliable AI system behaviour.

Design, develop, and deploy AI services on Microsoft Azure, leveraging services such as Azure OpenAI, Azure Functions, Azure Kubernetes Service (AKS), and related cloud services.

Design and run evaluation pipelines and experimentation frameworks to continuously improve AI agent accuracy, reliability, and performance.

Collaborate with product managers, and engineering teams to translate business problems into AI‑driven solutions.

Skills & Experience Req-

Design and develop modern, scalable front‑end applications using React and TypeScript, delivering intuitive interfaces for AI‑driven workflows, multi‑agent interactions, and complex task orchestration dashboards.

Real‑time Response handling as streaming chat responses, token‑by‑token updates, agent tool traces, and live execution timelines- using WebSocket, Socket.IO or Server‑Sent Events (SSE).

Develop front‑end components that visualize agentic AI systems, including reasoning steps, tool invocations, graphs and planning timelines.