Lead Backend Developer - AI API & Orchestration

EPAM Systems; United States; Remote; USD 140,000 - 190,000; Full time

Benefits offered by this job

Healthcare benefits

Paid time off

Upskilling & certification courses

LinkedIn Learning access

Global career opportunities

Job summary

EPAM Systems, Inc. is seeking a Lead Backend Developer to deliver secure, scalable AI-driven API services and orchestrate LLM workflows within AI Pods.

You will connect language models to internal systems, vector databases, and external tools via orchestration frameworks, treating LLMs as distributed components. You will design backend services and LLm layers, ensure reliability, security, observability, and cost awareness.

Qualifications

• 5+ years backend experience with microservices and distributed systems.
• Proficiency in Python to build high-performance cloud-native APIs.
• Experience with AWS and container orchestration (Docker, ECS/EKS).
• Strong API design and secure coding practices.
• English proficiency at B2 level or higher.
• Familiarity with AI SDKs and vector databases is a plus.

Responsibilities

• Design and build backend API services and LLm orchestration layers.
• Own API contracts and service reliability end-to-end.
• Integrate LLMs with systems, observability, fallback handling, and cost awareness.
• Develop RAG pipelines for document ingestion, chunking, embedding, and retrieval.
• Build reusable orchestration frameworks for internal consumption by developers.
• Ensure security, privacy, and enterprise-grade observability and test coverage.
• Collaborate with frontend, data, and infrastructure teams.

Skills

Python

Distributed systems

Backend engineering

API design

Security best practices

English communication

Tools

AWS

Docker

ECS/EKS

LangChain

LangGraph

MCP

OpenAI SDK

Vector databases

LangSmith

Job description

EPAM Systems, Inc. is seeking a Lead Backend Developer to deliver secure, scalable AI-driven API services and orchestrate LLM workflows within AI Pods.

You will connect language models to internal systems, vector databases, and external tools via orchestration frameworks, treating LLMs as distributed components. You will design backend services and LLm layers, ensure reliability, security, observability, and cost awareness.