Remote AI Solution Architect - Production-Grade LLM & RAG

EPAM Systems Inc; Austin (TX); Remote; USD 150,000 - 200,000; Full time

Benefits offered by this job

Medical/Dental Insurance

Health Savings Account

Flexible Spending Accounts

Life and AD&D Insurance

Employee Stock Purchase Program

Discretionary bonus program

401(k)

Job summary

EPAM Systems, Inc. seeks a Solution Architect embedded with client teams to design AI-powered, production-ready architectures (LLM, RAG, and agentic solutions) with governance and evaluation mechanisms.

You will collaborate across business and engineering stakeholders to drive pilots from concept to production, ensuring security, observability, and scalable deployment in complex environments.

Qualifications

• Production-ready AI solution architectures including LLM, RAG and agentic workflows.
• Governance, evaluation and publishable patterns with working code.
• Hands-on Python coding to prototype and validate AI-assisted implementations.

Responsibilities

• Partner with client business, product, engineering, security, and operations teams to capture requirements and record architecture decisions.
• Design end-to-end AI solution architectures covering RAG, agentic workflows and MCP tool integration, IAM and enterprise integration patterns.
• Build Cloud FinOps cost models linking feature cost, usage, quality and business value.
• Document AI governance evidence for each agent, including autonomy limits, tool permissions, human checkpoints and rollback controls.
• Model domain knowledge graphs and apply GraphRAG to improve retrieval.

Skills

Solution architecture

Cloud architecture

Python coding

LLM knowledge

Tools

APIs

MCP

Job description

EPAM Systems, Inc. seeks a Solution Architect embedded with client teams to design AI-powered, production-ready architectures (LLM, RAG, and agentic solutions) with governance and evaluation mechanisms.

You will collaborate across business and engineering stakeholders to drive pilots from concept to production, ensuring security, observability, and scalable deployment in complex environments.