Chief Agentic AI Engineer

EPAM Systems; Argentina; Remote; ARS 3,500,000 - 6,000,000; Full time

Benefits offered by this job

Healthcare benefits

Paid time off

Sick leave

Upskilling and certification courses

LinkedIn Learning access

Global career opportunities

Volunteer opportunities

Job summary

EPAM Systems seeks a Chief Agentic AI Engineer to design and operate scalable autonomous agent systems. You will shape runtimes, memory, identity, tools, and observability while guiding production-grade deployments with AWS Bedrock AgentCore and agentic frameworks.

You will lead architectural decisions, implement guardrails, evals, and reliability, and collaborate with global teams to ensure secure, efficient, and cost-aware agent operations across complex multi-step engagements.

Qualifications

• 7+ years of production software experience.
• 2+ years shipping LLM-based agents to production.
• Proficient in Python and agent frameworks.
• Experience with AWS Bedrock AgentCore primitives.

Responsibilities

• Define architecture for autonomous agents across runtime, memory, identity, tools, observability.
• Champion use of AWS Bedrock AgentCore and SDKs in production deployments.
• Develop and maintain memory and context-management systems.

Skills

Python

LLM agents

Agent frameworks

AWS Bedrock

Observability

Memory architectures

Guardrails

English (B2)

Tools

Strands

LangGraph

Claude Agent SDK

OpenAI Agents SDK

CrewAI

AWS Bedrock AgentCore

Job description

We are looking for a Chief Agentic AI Engineer to build autonomous agent systems at scale and steer decisions across runtime, memory, identity, tools, and observability. You will lead production-grade deployments using AWS Bedrock AgentCore and agentic frameworks, shaping guardrails, evals, and reliability.ResponsibilitiesDefine the architecture for building, deploying, and operating autonomous agents across runtime, memory, identity, tools, and observabilityChampion the use of AWS Bedrock AgentCore and the Strands Agents SDK across agent harnesses and production deploymentsArchitect long-term memory and context-management systems that remain robust across multi-step engagementsDevelop and maintain MCP servers and tool integrations agents call, including recon, scanners, exploit primitives, and custom internal servicesOptimize reliability, cost, and latency of agent reasoningEstablish standards for evals, tracing, and guardrailsRequirements7+ years of experience building production software, including 2+ year shipping LLM-based agents to productionExpert proficiency in Python and 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 demonstrated ability to ramp up quicklyDeep understanding of MCP, tool use, prompt/context engineering, memory architectures, and agent evaluationDemonstrated capability to design for production, including observability, guardrails, retries, cost control, and security boundariesEnglish proficiency at B2 level or higherNice to havePrior background 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