Role & responsibilities

We are seeking a highly experienced Java Architect with AI/GenAI expertise to design and deliver next-generation enterprise applications leveraging Java microservices, cloud-native architecture, and Generative AI technologies. The candidate will drive architecture decisions, define technology roadmaps, and build scalable AI-enabled solutions for enterprise customers.

Key Responsibilities:

Architecture & Design
Define end-to-end solution architecture for enterprise-scale applications.
Design microservices-based, event-driven, and API-first architectures.
Lead architecture reviews, technology selection, and governance.
Ensure scalability, security, resiliency, and performance of platforms.

Java Technology Leadership
Architect solutions using Java, Spring Boot, Spring Cloud, REST APIs, Kafka, and distributed systems.
Drive cloud-native adoption using Azure/AWS.
Establish engineering standards, CI/CD practices, and DevSecOps controls.
Mentor development teams and provide technical leadership.

AI / GenAI Responsibilities
Design and implement GenAI-powered enterprise applications.
Build and deploy RAG (Retrieval Augmented Generation) based solutions.
Architect AI agents using LangChain, LangGraph, CrewAI, AutoGen, or similar frameworks.




Integrate LLMs such as Azure OpenAI, OpenAI, Anthropic, or AWS Bedrock.
Design Vector Database architecture using Pinecone, ChromaDB, FAISS, or Azure AI Search.
Define prompt engineering strategies, evaluation frameworks, and AI guardrails.
Drive responsible AI, security, observability, and governance practices.

Mandatory Skills

Core Architecture Skills
Java 17+
Spring Boot / Spring Cloud
Microservices Architecture
REST APIs & API Gateway
Kafka / Event Streaming
Distributed System Design
Design Patterns & Enterprise Architecture
Docker & Kubernetes/OpenShift
CI/CD (Jenkins, GitHub Actions, Azure DevOps)

AI / GenAI Skills
LLM Architecture
RAG Frameworks
Prompt Engineering
LangChain / LangGraph
CrewAI / AutoGen
Vector Databases (FAISS, Pinecone, Chroma)
AI Agent Architecture
Azure OpenAI / AWS Bedrock

Cloud
Azure (Preferred) or AWS
Kubernetes
Serverless Architecture
Monitoring & Observability

Preferred Skills
Python for AI integrations.
Knowledge of AI governance and model lifecycle management.
Experience with BFSI domain.
Exposure to multi-agent systems and autonomous workflows.

📌 Java Architect Ai Genai Solutions Maharashtra
🏢 Tata Consultancy Services
📍 Maharashtra