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# Solution Architect, Forward Deployed AI

- **Company:** EPAM Systems, Inc.
- **Location:** Chicago, IL, United States (Remote available)
- **Salary:** $150,000.0 - $200,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Business Software, Cloud Computing, Cloud Engineering, Graph Database, Identity and Access Management, Python (Programming Language), Data Streaming, Enterprise Application Integration, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Agentic-AI, Enterprise Integration, Machine Learning Operations, Virtual Agents, Evaluation of Large Language Models, Graph RAG, Model Context Protocol, Intelligent Document Processing, Microservices
- **Published:** November 5, 2026
- **Apply:** https://www.chicagocareersite.com/job.asp?id=3496671657&tx=FR9794FFR&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* Client-facing solution architecture experience with business software or AI solutions that reached production, at either Solution Architect I level (own a bounded design with senior review) or Solution Architect II level (independently lead a complete client AI solution)
 * Strong fundamentals in cloud computing architecture, microservice architecture, APIs, data flows, Identity and Access Management, and enterprise integration patterns
 * Practical knowledge of LLM applications, Prompt Engineering, RAG, AI agent frameworks, tool calling through MCP, and agent orchestration
 * Recent hands-on Python coding to prototype, inspect failures, and validate AI-assisted implementation work
 * Experience defining LLM evaluation, AI observability, LLM security controls, and production quality attributes, plus an understanding of AI Governance, including agent permissions, autonomy, human oversight, auditability, and enterprise risk
 * Clear architecture documentation and strong communication with business and technical stakeholders, with comfort working on-site amid ambiguity (regulated-industry and Cloud FinOps exposure is a plus)

## Description

* Partner with client business, product, engineering, security, and operations teams to resolve requirements and record architecture decisions
 * Design end-to-end AI solution architectures covering RAG, agentic workflows and orchestration, Model Context Protocol (MCP) tool integration, Identity and Access Management, enterprise integration, LLM security, AI observability, and LLM evaluation
 * Build Cloud FinOps cost models that link feature cost, usage, quality, and expected business value
 * Document AI governance evidence for each agent, including autonomy limits, tool permissions, human checkpoints, evaluation and testing results, and rollback controls
 * Model domain Knowledge Graph slices covering entities, relationships, business constraints, provenance, and owners, applying GraphRAG where relationships improve retrieval
 * Build Python reference implementations and technical proofs with Forward Deployed Engineers, then preserve architecture integrity through the pilot-to-production transition under Architecture Governance and publish reusable patterns