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