Overview

We are looking for a Lead Backend Developer to spearhead our AI Pods initiative and drive the engineering of intelligent API services and agentic workflows at scale. In this leadership role, you will architect systems where language models interact seamlessly with internal platforms, vector stores and third-party tools through orchestration frameworks. You will set the technical direction for treating LLMs as first-class citizens within secure, scalable distributed architectures while mentoring engineers and shaping platform-wide engineering excellence.

Responsibilities

  • Lead the architectural design of backend API services and LLM orchestration layers across the pod
  • Oversight of complex RAG pipeline development covering document ingestion, chunking, embedding strategies and retrieval optimization
  • Drive the integration of agent tooling leveraging LangChain, LangGraph and MCP (Model Context Protocol)
  • Establish standards for security, privacy, enterprise-grade observability and comprehensive test coverage across backend workflows
  • Define architecture decisions and engineering best practices that scale across teams
  • Partnership with frontend engineers, data engineers and infrastructure teams to deliver cohesive solutions
  • Mentor and guide engineers, fostering a culture of technical rigor and continuous improvement
  • Champion reusable orchestration frameworks and platform logic for downstream developer adoption
  • Guarantee graceful failure handling for AI edge cases while owning API contracts end-to-end
  • Evaluate emerging AI technologies and translate them into actionable engineering roadmaps

Requirements

  • 5+ years of backend engineering experience with deep focus on microservices and distributed systems
  • Strong proficiency in Python applied to high-performance backend services and cloud-native APIs
  • Expertise in AWS, Docker and ECS/EKS
  • Competency in designing and delivering RESTful APIs
  • Understanding of secure coding practices alongside solid auth/authz foundations
  • Demonstrated technical leadership experience driving architecture and mentoring engineering teams
  • Upper-Intermediate English language proficiency (B2)

Nice to have

  • Hands-on production experience with AI SDKs such as OpenAI, Anthropic/Claude or AWS Bedrock
  • Practical background in vector databases (Amazon Kendra, OpenSearch), embedding techniques and retrieval systems
  • Showcase of work with agentic frameworks including LangChain, LlamaIndex or LangGraph
  • Familiarity with AI evaluation tooling and real-time APM platforms like LangSmith, Langfuse or Arize
  • Working knowledge of React, TypeScript and large-scale EKS deployments
  • Flexibility to use secondary languages such as Java, Node.js or Go alongside exposure to MCP interoperability patterns and identity domains (IAM, CIAM)

[GTS] Benefits (generic, except India)

  • International projects with top brands
  • Work with global teams of highly skilled, diverse peers
  • Healthcare benefits
  • Employee financial programs
  • Paid time off and sick leave
  • Upskilling, reskilling and certification courses
  • Unlimited access to the LinkedIn Learning library and 22,000+ courses
  • Global career opportunities
  • Volunteer and community involvement opportunities
  • EPAM Employee Groups
  • Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn