Remote AI Systems Architect & Principal Engineer

EPAM Systems

Chicago (IL)

Remote

USD 140,000 - 165,000

Full time

10 days ago

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Benefits offered by this job

Medical, Dental and Vision Insurance (

Health Savings Account

Flexible Spending Accounts

Short-Term and Long-Term Disability

Life and AD&D Insurance

Employee Assistance Program

LinkedIn Learning access

401(k) Retirement Savings Plan

Paid Time Off (15-25 days)

Paid Holidays

Legal Plan and Identity Theft

Pet Insurance

Employee Stock Purchase Program

Discretionary annual bonus program

Discretionary Long-Term Incentive (LTI

Job summary

EPAM Systems, Inc. is seeking an Architect / Principal Software Engineer to lead the technical direction of our AI Engineering pods.

You will split your time between hands-on engineering (about 30% to 40% prototyping core workflows, building reference implementations, and reviewing code) and higher-level system architecture, technical standards, and mentorship across teams. You will collaborate with US-based Product, Security, Data, and Infrastructure teams to ensure our agentic systems are

Qualifications

10+ years of software engineering experience designing, scaling, and operating distributed backend systems.
6+ years of Python experience with FastAPI, AsyncIO, and modern typing practices.
3+ years building production AI systems with LLMs and LangChain/OpenAI APIs.
Hands-on experience with LangGraph or similar stateful agent frameworks, managing state graphs and loops.
3 to 4 years of React and TypeScript experience, able to review UI code and ensure streaming APIs work with the web client.
Production AWS experience (EKS/ECS, Lambda, Bedrock, S3), Docker, and Terraform or OpenTofu.
Authentication and security fundamentals (OAuth 2.0, OIDC) and secure credential handling.

Responsibilities

Set architectural direction across multiple AI pods, balancing model capabilities, cost, latency, and complexity.
Spend about one third of time coding backend AI services and defining integration contracts with frontend teams.
Design agent workflows with streaming responses and low latency for chat and automated tasks.
Establish shared standards for Model Context Protocol servers, tool schemas, and context management.
Collaborate with Security and Infra to enforce least-privilege tool execution, tenant isolation, and secret handling.
Define observability requirements and SLIs, including tracing with LangSmith or Arize Phoenix.
Mentor Staff and Senior engineers through design reviews and technical guidance.