Senior Python AI Engineer: Multi-Agent & RAG Systems

EPAM Systems; México; On-site; MXN 600,000 - 1,200,000; Full time

Benefits offered by this job

Healthcare benefits

Financial programs

Paid time off

Sick leave

Upskilling programs

LinkedIn Learning access

Global career opportunities

Volunteer opportunities

Award-winning culture

Job summary

EPAM Systems is seeking engineers to advance Python-based AI products by building scalable, secure agentic systems. You will implement multi-agent orchestration with LangChain and LangGraph, develop RAG pipelines, and integrate MCP while leveraging AWS Bedrock and GCP Vertex AI.

The role involves architecting scalable data-driven applications, collaborating with multinational teams, and coaching peers to deliver high-quality code across the full SDLC.

Qualifications

• 3+ years of Python engineering with production AI systems.

Responsibilities

• Architect and deliver scalable systems enabling data-driven intelligent applications.
• Translate complex technical ideas into working implementations aligned with objectives.
• Coordinate with multidisciplinary teams to clarify needs and ensure strong delivery.
• Develop readable, maintainable code following industry standards and documentation.
• Diagnose & address issues throughout the full software lifecycle.
• Perform peer code reviews and provide actionable feedback.
• Explore new tech trends and propose infrastructure upgrades.
• Contribute to architectural planning shaping future roadmaps.
• Coach junior engineers and spread technical expertise.
• Ensure solutions meet scalability, performance and long-term maintainability.

Skills

Python engineering

LangChain

LangGraph

MCP

RAG pipelines

Prompt engineering

Guardrails

Knowledge graphs

AWS Bedrock

GCP Vertex AI

Cross-agent orchestration

Tools

AWS Bedrock

GCP Vertex AI

Job description

EPAM Systems is seeking engineers to advance Python-based AI products by building scalable, secure agentic systems. You will implement multi-agent orchestration with LangChain and LangGraph, develop RAG pipelines, and integrate MCP while leveraging AWS Bedrock and GCP Vertex AI.

The role involves architecting scalable data-driven applications, collaborating with multinational teams, and coaching peers to deliver high-quality code across the full SDLC.