Ramanathapuram Coimbatore Tamil Nadu Quality solution architect Jobs – 142 Open Jobs Today

Senior Java Engineer - AI Native
EPAM Systems, Inc. —Coimbatore, Tamil Nadu
- Azure
- English
- Java
- Health insurance
- Paid time off

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Senior Java Engineer - AI Native
EPAM Systems, Inc. —Coimbatore, Tamil Nadu
Hands-on experience building and deploying at least one MCP server that exposes APIs, tools or data sources to an LLM agent.

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Senior Java Engineer - AI Native

EPAM Systems, Inc. -
Coimbatore, Tamil Nadu

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Job details

Benefits

Health insurance
Paid time off

Qualifications

Jira
Spring Boot
CI/CD
Azure
Law
MCP
Kubernetes
Relational databases
Enterprise Software
NoSQL
Git
English
MongoDB
Java
Master's degree
Databases
Microservices
AWS
Docker
Confluence
PostgreSQL
Continuous integration
Redis
RabbitMQ
REST
GitHub
APIs
ServiceNow
Kafka
AI
Jenkins
GitLab
Spring framework
MySQL
Spring MVC
SDLC

Full job description

EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

We are looking for a Senior Java Engineer – AI Native to join our team and drive the design and delivery of scalable Java applications while embedding AI-native practices across the full software development lifecycle. This role combines deep Java engineering expertise with hands-on experience building agentic pipelines and MCP integrations that connect enterprise systems to LLM-based agents.

The position requires 3 days of work from the office.

Responsibilities

Design, develop and maintain scalable Java applications using Spring Boot and microservices architecture, owning features end-to-end with a high degree of autonomy
Build and deploy Model Context Protocol (MCP) servers that expose Java services, databases or internal tools to LLM-based agents, enabling agents to act on live enterprise data and systems
Architect and implement end-to-end agentic SDLC pipelines including automated specification drafting, AI-driven code generation, intelligent test creation, CI/CD integration and deployment validation orchestrated by AI agents
Integrate agentic pipelines with enterprise tools and platforms such as Jira, Confluence, GitHub and ServiceNow via MCP connectors or REST/event-driven APIs
Use AI coding assistants and frontier LLMs across the full development lifecycle daily and critically evaluate AI outputs for correctness, security and edge cases before code commits
Bring an AI-first mindset to automate repetitive engineering tasks, measure outcomes rather than activity and identify AI-leverage opportunities within the delivery area
Contribute to the team's shared library of prompt templates, reusable agent patterns and MCP connectors
Conduct code and architecture reviews and mentor Junior and Mid-level engineers in Java best practices and AI-native engineering methods
Maintain strong automated test coverage across unit, integration, contract and AI-generated tests along with healthy CI/CD pipeline practices
Track frontier developments such as new model releases, emerging agent frameworks and new MCP connectors, and bring relevant changes back to the team within weeks

Requirements

5–10 years of hands-on Java development experience in production environments
Proficiency in Spring Boot, Spring MVC and Spring Security with RESTful API design
Experience with microservices and event-driven patterns using Kafka or RabbitMQ
Background in cloud platforms such as AWS, GCP or Azure including Docker and Kubernetes containerization
Knowledge of relational databases such as PostgreSQL and MySQL alongside NoSQL databases such as MongoDB and Redis
Familiarity with CI/CD pipelines including Jenkins, GitHub Actions and GitLab CI and DevOps engineering practices
Active daily use of AI coding assistants such as GitHub Copilot, Cursor or Claude Code and frontier LLMs, applied fluently rather than experimentally
Hands-on experience building and deploying at least one MCP server that exposes APIs, tools or data sources to an LLM agent
Showcase of designing or implementing an agentic workflow or pipeline that connects multiple tools or services via LLM-orchestrated agents
Capability to integrate agentic pipelines with enterprise systems via MCP or REST/event APIs through direct hands-on build experience
Working knowledge of at least one agent orchestration framework such as LangChain, LangGraph or CrewAI
Understanding of how to critically evaluate AI-generated code, identifying correctness issues, security gaps and performance problems, along with genuine learning agility reflected in evolving engineering practice over the last 6–12 months due to new AI tools or model capabilities
Upper-Intermediate English proficiency or above (B2+)

Nice to have

Experience building RAG (Retrieval-Augmented Generation) pipelines covering chunking, embedding and vector stores such as pgvector, Pinecone or Weaviate
Skills in prompt engineering for development contexts including systematic prompt design, evaluation harnesses and iteration workflows
Familiarity with LLM evaluation frameworks such as RAGAS or DeepEval to assess agent output quality
Experience with function calling and tool-use APIs across multiple frontier models from Anthropic, OpenAI and Google
Exposure to structured agentic SDLC methodologies such as spec-driven development with AI or specification hardening

We offer

Opportunity to work on technical challenges that may impact across geographies
Vast opportunities for self-development: online university, knowledge sharing opportunities globally, learning opportunities through external certifications
Opportunity to share your ideas on international platforms
Sponsored Tech Talks & Hackathons
Unlimited access to LinkedIn learning solutions
Possibility to relocate to any EPAM office for short and long-term projects
Focused individual development
Benefit package:
- Health benefits
- Retirement benefits
- Paid time off
- Flexible benefits
Forums to explore beyond work passion (CSR, photography, painting, sports, etc.)

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Senior Java Engineer - AI Native

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