Senior Backend Developer, AI Pods

About the Position

We are seeking a Senior Backend Developer to join our AI Pods team, building robust AI-powered API services and agentic workflows. This role focuses on language model interaction with internal systems, vector databases, and external tools via orchestration frameworks, treating LLMs as components in a secure, scalable distributed system.

Skills

• Python
• Amazon Web Services
• Gen AI Application Development
• REST API
• Vector Databases
• LangChain
• LangGraph
• LlamaIndex
• Model Context Protocol
• ReactJS
• Terraform

Responsibilities

• Design and build backend API services and LLM orchestration layers
• Own API contracts and service reliability end-to-end, ensuring AI edge cases fail gracefully
• Integrate LLMs using rigorous systems engineering, bake in evaluation, observability, fallback handling, and cost awareness
• Implement and maintain complex RAG pipelines, including document ingestion, chunking, embedding, and retrieval optimization
• Develop and connect agent tools using LangChain, LangGraph, and potentially MCP (Model Context Protocol)
• Build reliable, reusable orchestration frameworks and logic for downstream developer consumption
• Ensure security, privacy, enterprise-grade observability, and test coverage across all backend workflows
• Contribute to architecture decisions and engineering standards within the pod
• Collaborate with frontend engineers, data engineers, and infrastructure teams

Requirements

• 3+ years of backend engineering experience, focused on microservices and distributed systems
• Proficiency in Python for high-performance backend services and cloud-native APIs
• Familiarity with AWS, Docker, and ECS/EKS
• Knowledge of RESTful APIs
• Understanding of secure coding practices and strong auth/authz fundamentals
• English proficiency at B2 level or higher

Nice to Have

• 1+ years of hands-on experience with AI SDKs (OpenAI, Anthropic/Claude, AWS Bedrock, or equivalent) in production
• Practical experience with vector databases (Amazon Kendra, OpenSearch), embedding strategies, and retrieval systems
• Hands-on experience with LangChain, LlamaIndex, or LangGraph
• Familiarity with AI evaluation tooling or real-time APM (LangSmith, Langfuse, Arize)
• Skills in React and TypeScript
• Experience deploying to EKS environments at scale
• Understanding of agent interoperability patterns (MCP)
• Knowledge of identity/security domain (IAM, CIAM)
• Flexibility to use secondary languages such as Java, Node.js, or Go

We Offer

• 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