Senior AI Backend Engineer: LLM Pipelines & Orchestration

EPAM Systems, Inc.; United States; Remote; USD 120,000 - 190,000; Full time

Benefits offered by this job

Healthcare benefits

Paid time off and sick leave

Upskilling, reskilling and certificate

Job summary

EPAM Systems, Inc. is seeking a Senior Backend Developer to join its AI Pods team, building robust AI-powered API services and agentic workflows. You will design and operate backend services, orchestrate LLMs, and implement resilient RAG pipelines.

Collaborate with frontend, data, and infra teams to ensure security, observability, and scalable systems while advancing architectural standards across the pod.

Qualifications

• 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
• English proficiency at B2 level or higher.

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.
• Build reliable, reusable orchestration frameworks and logic for downstream developer consumption.
• Ensure security, privacy, enterprise-grade observability, and test coverage across all backend workflows.
• Collaborate with frontend engineers, data engineers, and infrastructure teams and contribute to architecture decisions and standards.

Job description

EPAM Systems, Inc. is seeking a Senior Backend Developer to join its AI Pods team, building robust AI-powered API services and agentic workflows. You will design and operate backend services, orchestrate LLMs, and implement resilient RAG pipelines.

Collaborate with frontend, data, and infra teams to ensure security, observability, and scalable systems while advancing architectural standards across the pod.