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 seeking a Senior Java Engineer – AI Native to design and build scalable Java applications while pioneering AI-driven engineering practices. In this role, you will own features end-to-end, build Model Context Protocol servers, and integrate agentic pipelines with enterprise systems, using frontier LLMs and AI coding assistants every day to deliver high-quality software.
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
-
Develop 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, ServiceNow and observability stacks via MCP connectors or REST/event-driven APIs
-
Leverage AI coding assistants and frontier LLMs across the full development lifecycle, critically evaluating AI outputs for correctness, security and edge cases before committing
-
Apply an AI-first mindset to automate repetitive engineering tasks, measure outcomes rather than activity and identify AI-leverage opportunities within your delivery area
-
Contribute to the team's shared library of prompt templates, reusable agent patterns and MCP connectors
-
Conduct code and architecture reviews while mentoring 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 alongside 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 in production environments
-
Proficiency in Spring Boot, Spring MVC and Spring Security with RESTful API design
-
Experience with microservices and event-driven patterns such as Kafka or RabbitMQ
-
Cloud platform expertise in AWS, GCP or Azure including containerization with Docker and Kubernetes
-
Knowledge of relational databases (PostgreSQL, MySQL) and NoSQL databases (MongoDB, Redis)
-
Skills in CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI) and DevOps engineering practices
-
Active daily use of AI coding assistants (GitHub Copilot, Cursor, Claude Code) and frontier LLMs in a fluent, not experimental, capacity
-
Hands-on experience building and deploying at least one MCP server exposing APIs, tools or data sources to an LLM agent
-
Demonstrated experience 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
-
Familiarity with at least one agent orchestration framework such as LangChain, LangGraph, CrewAI, AutoGen or Spring AI Agents
-
Strong critical evaluation of AI-generated code to identify correctness issues, security gaps and performance problems
-
Genuine learning agility to describe how your engineering practice changed meaningfully in the last 6–12 months due to new AI tools or model capabilities
-
English proficiency at Upper-Intermediate or above (B2+)
Nice to have
-
Experience building RAG pipelines including chunking, embedding and vector stores (pgvector, Pinecone, Weaviate)
-
Prompt engineering skills for development contexts including systematic prompt design, evaluation harnesses and iteration workflows
-
Familiarity with LLM evaluation frameworks (RAGAS, DeepEval) to assess agent output quality
-
Experience with function calling and tool-use APIs across multiple frontier models (Anthropic, OpenAI, 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.)
