We are looking for a Senior Backend Developer with Python and AI expertise to build 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. You will own API contracts and service reliability end-to-end, ensuring AI edge cases fail gracefully, while integrating LLMs using rigorous systems engineering with built-in evaluation, observability, fallback handling, and cost awareness.
Responsibilities
-
Design and build backend API services and LLM orchestration layers
-
Develop reliable, reusable orchestration frameworks and logic for downstream developer consumption
-
Implement and maintain complex RAG pipelines, including document ingestion, chunking, embedding, and retrieval optimization
-
Build and connect agent tools using LangChain, LangGraph, and potentially MCP (Model Context Protocol)
-
Integrate LLMs with rigorous systems engineering, embedding evaluation, observability, fallback handling, and cost awareness
-
Ensure security, privacy, enterprise-grade observability, and test coverage for all backend workflows
-
Own API contracts and service reliability end-to-end, ensuring AI edge cases fail gracefully
-
Contribute to architecture decisions and engineering standards within the pod
-
Collaborate with frontend engineers, data engineers, and infrastructure teams
Requirements
-
Strong backend engineering experience, focused on microservices and distributed systems
-
3+ years of experience in Python for high-performance backend services and cloud-native APIs
-
Expertise in AWS
-
Familiarity with Docker and ECS/EKS
-
Skills in building RESTful APIs and working with LangChain
-
Knowledge of secure coding practices and strong auth/authz fundamentals
-
English level of minimum B2 (Upper-Intermediate) for effective communication
Nice to have
-
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
-
Familiarity with LlamaIndex, LangGraph, or agent interoperability patterns (MCP)
-
Background in AI evaluation tooling or real-time APM (LangSmith, Langfuse, Arize)
-
Experience with React and TypeScript
-
Understanding of identity/security domains (IAM, CIAM), plus deploying to EKS environments at scale
-
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
