Role & responsibilities We are seeking a highly experienced Java Architect with AI/GenAIexpertise 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.

Role : 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.

📌 Software Engineer (Pune)
🏢 Tata Consultancy Services
📍 Pune