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Technical Lead Engineer, Artificial Intelligence (Chicago)
Technical Lead Engineer, Artificial Intelligence (Chicago)Request Technology, LLC • Chicago, IL, United States
Technical Lead Engineer, Artificial Intelligence (Chicago)

Technical Lead Engineer, Artificial Intelligence (Chicago)

Request Technology, LLC • Chicago, IL, United States
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  • [job_card.full_time]
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Technical Lead Engineer, Artificial Intelligence

Salary : Open + Bonus

Location : Chicago, IL

Hybrid : 3 days onsite 2 days remote

  • We are unable to provide sponsorship for this role

Qualifications

  • Bachelor's or Master's degree in Computer Science or related technical field
  • 10+ years software engineering / systems architecture experience with strong technical leadership
  • 5+ years as senior technical contributor on complex production systems
  • Expert in Python and proficient in SQL
  • System design expertise : monolithic and microservice architecture, distributed systems, event-driven architecture, APIs
  • Hands-on experience in data (e.g., data engineering, data pipelines, data transformation)
  • Experience with LLMs and familiarity with multiple frontier lab models (e.g., Gemini, Claude, GPT)
  • Familiarity of risk vectors in AI applications including hallucinations, bias, prompt injection, data privacy
  • Cloud platforms / technologies : AWS, Docker, Kubernetes, CI / CD, Terraform
  • Experience with RAG architecture and context engineering
  • Familiarity with diverse LLM provider APIs and experience connecting agents to systems
  • Responsibilities

  • Partner with the Executive Director, AI Engineering to help define and execute on AI technical roadmap
  • Lead and partner on the architecture of scalable systems incorporating LLMs and AI into organizational processes and infrastructure
  • Design and build production applications in support of organizational use cases
  • Provide technical mentorship to junior engineers on engineering best practices and system design (no direct reports)
  • Conduct code / architectural reviews ensuring production readiness, safety, and adherence to high security and compliance standards
  • Implement testing, evaluation, and monitoring frameworks for AI systems including hallucination detection and bias assessment
  • Establish safety guardrails and responsible AI practices for LLM applications in a regulated environment
  • Connect AI agents to organizational systems and workflows
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