Applied AI Engineer at Parts Town
Addison
$133,953–$157,542from the description
Aug 10, 2026
Addison
Sep 24, 2026
What this job asks for AI summary
This role is responsible for building and operating production-grade AI systems — including LLM-based pipelines, RAG workflows, inference services, and APIs — integrated into core business processes at a large parts distributor. The engineer works across cloud and enterprise data platforms, partners with business stakeholders to frame problems, and contributes to architectural and evaluation decisions. It suits a hands-on software engineer with meaningful ML/AI deployment experience.
Senior level · Chicago-Naperville-Elgin, IL-IN-WI · Full-time
“or” means any one of them counts — you don't need all of them.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 220 people in the Chicago-Naperville-Elgin, IL-IN-WI area plausibly meet what this posting asks for (software developers). range 170–290
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Rare in this occupation — lead with these, and say what you built with them.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $137,335 (middle half $106,829–$171,337). This posting is about at that midpoint.
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Aug 12, 2026. It is a model, not a headcount.
Why we read it this way (7)
The role title 'Applied AI Engineer' carries no explicit seniority level, but the scope — owning production AI systems, contributing to architectural decisions, and shaping long-term AI strategy — is consistent with a Senior individual contributor.
SOC classification is a genuine judgment call: the role is primarily software engineering (building APIs, inference services, pipelines) with a strong ML/AI flavor. 15-1252 Software Developers is the primary code; 15-2051 Data Scientists is the runner-up given the ML modeling and evaluation framework work.
Cloud platform is required but no specific provider is named; AWS, Azure, and GCP are listed as alternatives.
'ML/AI production deployment' is a role-level requirement stated without naming a specific tool — it is captured here as a skill because the posting explicitly gates on it as a concrete capability, not merely a generic concept.
Bonus-points items (enterprise data platforms, semantic/ontology modeling, monitoring/observability, MLOps) appear under an explicitly optional 'Bonus points if' section and are marked preferred accordingly.
The posting describes a hybrid work schedule; fully remote is not offered.
Ignored 3 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): prompt orchestration, ML/AI production deployment, semantic modeling.
Read the full posting
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