Senior AI Agent Platform Engineer

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

Job summary

EPAM Systems Inc. seeks a Senior DevOps/Platform Engineer to own the agentic versioning, promotion workflow, and rollback patterns across the agent estate in a cloud-native Enterprise Agent Development Platform on AWS.

You will standardize agent development, runtime architecture, and observability, enabling teams to deploy and observe AI agents at scale while enforcing security and governance. Strong MLOps/DevOps background required.

Qualifications

• 5+ years of experience in MLOps or DevOps engineering with AI/ML systems.
• Hands-on experience with deployment, promotion, or rollback workflows for AI agents.
• Experience in versioning and lifecycle management for LLM agents or ML models.
• Experience in immutable artifact versioning at enterprise scale using ECR and model registries.
• Experience in CI/CD pipeline design with quality gates for AI systems.
• English proficiency at B2 level or higher.

Responsibilities

• Define and maintain the agentic versioning model and policy associations.
• Manage AWS AgentCore Runtime versioning and endpoint management.
• Design and enforce the agent promotion workflow from dev to prod with quality gates.
• Establish agent rollback patterns that restore previous agent versions.
• Configure AWS ECR tagging, policies, and image signing to preserve immutability.
• Integrate with the Agent Registry to auto-register agent versions and metadata.
• Collaborate with engineering teams to standardize versioning and lifecycle practices across the estate.

Skills

MLOps

DevOps

AWS

CI/CD

ECR

Agent lifecycle

Versioning

Observability

Security

Tools

AWS AgentCore Runtime

LangGraph

LangSmith

PromptLayer

LangGraph

Job description

EPAM Systems Inc. seeks a Senior DevOps/Platform Engineer to own the agentic versioning, promotion workflow, and rollback patterns across the agent estate in a cloud-native Enterprise Agent Development Platform on AWS.

You will standardize agent development, runtime architecture, and observability, enabling teams to deploy and observe AI agents at scale while enforcing security and governance. Strong MLOps/DevOps background required.