Applied AI Engineer — Production ML & LLMs (Hybrid)

Parts Town

Addison (IL)

Hybrid

USD 134,000 - 158,000

Full time

13 days ago

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Benefits offered by this job

Hybrid Work schedule
Quarterly profit-sharing bonus
Team member appreciation events and認n
Volunteer opportunities
Casual dress code
On demand pay options
Health, 401k, EAP and time away

Job summary

Parts Town is seeking an Applied AI Engineer to advance internal AI capabilities across cloud and enterprise platforms. You will own production-ready AI solutions and translate technical outcomes into business value while partnering with AI, Business, and Data teams.

The role emphasizes design of scalable AI systems, RAG pipelines, and evaluation frameworks. A hybrid work schedule and comprehensive benefits are offered, with a compensation range disclosed in the posting.

Qualifications

  • Strong Python skills with solid software engineering fundamentals and experience deploying ML/AI systems into production.
  • Experience building APIs or service-based architectures and working with LLM-based systems (RAG, prompt orchestration, eval frameworks).
  • Proven ability to operate in fast-evolving, ambiguous environments with ownership and accountability.

Responsibilities

  • Design, develop, and deploy LLM and ML-based AI solutions into production.
  • Build and maintain RAG pipelines, prompt orchestration workflows, and AI-driven automation systems.
  • Develop scalable inference services, APIs, and integration layers.
  • Investigate and resolve complex system and data challenges across AI pipelines.

Skills

Python
LLM workflows
API design
Cloud platforms
Production systems
Problem solving

Tools

APIs

Job description

Parts Town is seeking an Applied AI Engineer to advance internal AI capabilities across cloud and enterprise platforms. You will own production-ready AI solutions and translate technical outcomes into business value while partnering with AI, Business, and Data teams.

The role emphasizes design of scalable AI systems, RAG pipelines, and evaluation frameworks. A hybrid work schedule and comprehensive benefits are offered, with a compensation range disclosed in the posting.

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