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Artificial Intelligence Engineer

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Onsite

Artificial Intelligence Engineer

Request Technology, LLC

Artificial Intelligence Engineer

Skills

SQL QueriesDockerPythonAIAWS

1 month ago

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Important information


Contract type:

Permanent

Salary:

$150,000 – $160,000 / year

Location:

Chicago, IL, USA

Work mode:

Onsite

Published on:

20 September 2026

What they need


***We are unable to sponsor as this is a permanent full-time role***

***Hybrid, 3 days onsite, 2 days remote***

Responsibilities:

  • Own the design and delivery of agentic AI systems end-to-end, from architecture through production deployment
  • Architect agent orchestration patterns, tool and context integration, and evaluation pipelines for reliability in a regulated environment
  • Own AI infrastructure supporting AIRE's agents and applications on AWS, and contribute to the team's growing infrastructure self-sufficiency
  • Implement technical safeguards against AI-specific risks, including hallucination detection, prompt injection defense, and output validation, in collaboration with company AI Governance function
  • Build audit logging and human-in-the-loop checkpoints into agentic workflows so agent actions remain traceable and reviewable in a regulated environment

Qualifications:

  • Bachelor's degree in Computer Science, Engineering, or a related technical field; Master's preferred
  • 4-7 years of software engineering experience, with production AI/LLM systems experience preferred
  • Strong Python; proficient SQL; solid distributed systems and API design fundamentals
  • Hands-on experience building LLM-powered applications or agentic systems
  • Working knowledge of AI-specific risk areas (prompt injection, output validation, hallucination mitigation, data privacy), or demonstrated ability to build this expertise quickly
  • Cloud infrastructure experience (AWS preferred); comfort with Docker, CI/CD, and containerization fundamentals
  • Direct experience with Claude, the Anthropic API, or Claude.ai/Console
  • Experience designing agent orchestration or Model Context Protocol (MCP)-based integrations
  • Production experience operating LLM-powered applications or agentic systems at scale

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