Senior Agentic AI Engineer — Build Scalable Autonomous Agents

EPAM Systems

Argentina

Remote

ARS 136,660,000 - 227,766,000

Full time

2 days ago
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Benefits offered by this job

Healthcare benefits
Paid time off
Upskilling and certs
LinkedIn Learning access
Global career opportunities

Job summary

EPAM Systems, Inc. is seeking a Senior Agentic AI Engineer to architect, build, and run autonomous agent systems at scale. You will make key architectural decisions spanning runtime, memory, identity, tools, and observability for production AI systems.

You will lead adoption of AWS Bedrock AgentCore and Strands/LangGraph frameworks, develop memory and context-management, and improve reliability and cost efficiency of agent reasoning. Strong Python is required.

Qualifications

  • 3+ years building production software with at least 1 year deploying LLM-based agents.
  • Strong Python and hands-on experience with agentic frameworks.
  • Knowledge of AWS Bedrock AgentCore components and related tooling.
  • Solid grasp of memory, prompt engineering, and agent evaluation methods.
  • English proficiency at least B2 level.

Responsibilities

  • Architect autonomous agent systems spanning runtime, memory, identity, tools, and observability.
  • Develop MCP servers and tool integrations that agents rely on.
  • Improve reliability, cost-efficiency, and speed of agent reasoning.
  • Establish standards for evaluations, tracing, and guardrails.

Skills

Python
Agent frameworks
LLM deployment
Observability
Memory architecture

Tools

Strands
LangGraph
Claude SDK
OpenAI Agents SDK
CrewAI
AWS Bedrock AgentCore

Job description

EPAM Systems, Inc. is seeking a Senior Agentic AI Engineer to architect, build, and run autonomous agent systems at scale. You will make key architectural decisions spanning runtime, memory, identity, tools, and observability for production AI systems.

You will lead adoption of AWS Bedrock AgentCore and Strands/LangGraph frameworks, develop memory and context-management, and improve reliability and cost efficiency of agent reasoning. Strong Python is required.

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