Chief Agentic AI Engineer

EPAM Systems, Inc.; United States; Remote; USD 180,000 - 280,000; Full time

Benefits offered by this job

Healthcare benefits

Paid time off

Professional development

Job summary

EPAM Systems, Inc. seeks a Chief Agentic AI Engineer to architect, deliver, and run autonomous agent systems at scale with production-grade reliability.

You will shape end-to-end agentic workflows across runtime, memory, identity, tools, and observability while raising the bar for evaluation, tracing, and guardrails. Responsibilities define architecture for building, deploying, and operating autonomous agents, covering runtime, memory, identity, tools, and observability and champion adoption of

Qualifications

• 7+ years in production software development.
• 2+ years shipping LLM-based agents to production.
• Proficiency in Python and agentic frameworks.

Responsibilities

• Define architecture for autonomous agents across runtime, memory, identity, tools and observability.
• Architect long-term memory and context-management systems for multi-step engagements.
• Create and maintain MCP servers and tool integrations for agents.
• Optimize reliability, cost, latency and establish evals, tracing and guardrails.

Skills

Python

Agent framework

AWS Bedrock AgentCore

Memory architectures

Observability

Security boundaries

Prompt/context engineering

Tools

Strands

LangGraph

Claude Agent SDK

OpenAI Agents SDK

CrewAI

Job description

We are seeking a Chief Agentic AI Engineer to architect, deliver, and run autonomous agent systems at scale with production-grade reliability. You will shape end-to-end agentic workflows across runtime, memory, identity, tools, and observability while raising the bar for evaluation, tracing, and guardrails.ResponsibilitiesDefine architecture for building, deploying, and operating autonomous agents, covering runtime, memory, identity, tools, and observabilityChampion adoption of AWS Bedrock AgentCore and the Strands Agents SDK across agent harnesses and production deploymentsArchitect long-term memory and context-management systems that remain effective across multi-step engagementsCreate and maintain MCP servers and tool integrations agents call, including recon, scanners, exploit primitives, and custom internal servicesOptimize reliability, cost, and latency of agent reasoning, and establish standards for evals, tracing, and guardrailsRequirementsProven experience building production software, including 7+ years overall and 2+ years shipping LLM-based agents to productionExpert proficiency in Python with hands-on use of an agentic framework such as Strands, LangGraph, Claude Agent SDK, OpenAI Agents SDK, or CrewAIWorking knowledge of AWS Bedrock AgentCore primitives, including Runtime, Memory, Identity, Gateway, and Observability, or a demonstrated ability to ramp up quicklyDeep understanding of MCP, tool use, prompt/context engineering, memory architectures, and agent evaluationStrong production design skills spanning observability, guardrails, retries, cost control, and security boundariesEnglish proficiency at B2 (Upper-Intermediate) level or higherNice to haveExperience in application security, web pentesting, or red-teamingExposure to sandboxed code execution, browser agents, or autonomous tool orchestrationWe offerInternational projects with top brandsWork with global teams of highly skilled, diverse peersHealthcare benefitsEmployee financial programsPaid time off and sick leaveUpskilling, reskilling and certification coursesUnlimited access to the LinkedIn Learning library and 22,000+ coursesGlobal career opportunitiesVolunteer and community involvement opportunitiesEPAM Employee GroupsAward-winning culture recognized by Glassdoor, Newsweek and LinkedIn