Chief Agentic AI Engineer

EPAM Systems; Argentina; On-site; ARS 3,000,000 - 4,200,000; Full time

Benefits offered by this job

Healthcare benefits

Learning programs (upskilling)

Global teams and career opportunities

Paid time off

Job summary

EPAM Systems seeks a Chief Agentic AI Engineer to design, deploy, and operate autonomous agent systems at scale with production-grade reliability. You will shape end-to-end workflows across runtime, memory, identity, tools, and observability, raising standards for evaluation, tracing, and guardrails.

Responsibilities include architecting agent ecosystems, driving adoption of Bedrock AgentCore and Strands SDK, and building memory and context-management systems for multi-step engagements.

Qualifications

• 7+ years of software experience with 2+ years shipping production LLM agents.
• Proficiency in Python and agentic frameworks.
• Experience with agent memory, context, and observability.

Responsibilities

• Define architecture for autonomous agents across runtime, memory, identity, tools and observability.
• Champion adoption of AWS Bedrock AgentCore and Strands SDK in production.
• Architect long-term memory and context management for multi-step engagements.
• Create and maintain MCP servers and tool integrations for agent tooling and safety.
• Optimize reliability, cost and latency of agent reasoning; set evals and guardrails.

Skills

Python

Agent Frameworks

LLM Production

System Design

English B2+

Tools

Strands

LangGraph

Claude Agent SDK

OpenAI Agents SDK

CrewAI

AWS Bedrock AgentCore

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.

Responsibilities

• Define architecture for building, deploying, and operating autonomous agents, covering runtime, memory, identity, tools, and observability
• Champion adoption of AWS Bedrock AgentCore and the Strands Agents SDK across agent harnesses and production deployments
• Architect long-term memory and context-management systems that remain effective across multi-step engagements
• Create and maintain MCP servers and tool integrations agents call, including recon, scanners, exploit primitives, and custom internal services
• Optimize reliability, cost, and latency of agent reasoning, and establish standards for evals, tracing, and guardrails

Requirements

• Proven experience building production software, including 7+ years overall and 2+ years shipping LLM-based agents to production
• Expert proficiency in Python with hands-on use of an agentic framework such as Strands, LangGraph, Claude Agent SDK, OpenAI Agents SDK, or CrewAI
• Working knowledge of AWS Bedrock AgentCore primitives, including Runtime, Memory, Identity, Gateway, and Observability, or a demonstrated ability to ramp up quickly
• Deep understanding of MCP, tool use, prompt/context engineering, memory architectures, and agent evaluation
• Strong production design skills spanning observability, guardrails, retries, cost control, and security boundaries
• English proficiency at B2 (Upper-Intermediate) level or higher

Nice to have

• Experience in application security, web pentesting, or red-teaming
• Exposure to sandboxed code execution, browser agents, or autonomous tool orchestration

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