Lead Gen AI Engineer (Hybrid Work Schedule)

Information Technology Addison, Illinois Plattsburgh, New York Fort Wayne, Indiana


Description

Position at Parts Town

 

Lead Gen AI Engineer

 

See What We’re All About

As the fastest-growing distributor of restaurant equipment, HVAC and residential appliance parts, we like to do things a little differently. First, you need to understand and demonstrate our Core Values with safety being your first priority. That’s key. But we’re also looking for unique enthusiasm, high integrity, courage to embrace change…and if you know a few jokes, that puts you on the top of our list!

Do you have a genius-level knowledge of original equipment manufacturer parts? If not, no problem! We’re more interested in passionate people with fresh ideas from different backgrounds. That’s what keeps us at the top of our game. We’re proud that our workplace has been recognized for its growth and innovation on the Inc. 5000 list 15 years in a row and the Crain’s Fast 50 list ten times. We are honored to be voted by our Chicagoland team as a Chicago Tribune Top Workplace for the last four years.

If you’re ready to roll up your sleeves, go above and beyond and put your ambition to work, all while having some fun, let’s chat – Apply Today!

 

Perks

  • Parts Town Pride – check out our virtual tour and culture!
  • Quarterly profit-sharing bonus
  • Hybrid Work schedule
  • Team member appreciation events and recognition programs
  • Volunteer opportunities
  • Monthly IT stipend
  • Casual dress code
  • On-demand pay options: Access your pay as you earn it, to cover unexpected or even everyday expenses
  • All the traditional benefits like health insurance, 401k/401k match, employee assistance programs and time away – don’t worry, we’ve got you covered.

 

 

The Job at a Glance

The Data GenAI Engineer will design, prototype, and deliver generative AI solutions that leverage Parts Town’s enterprise data on GCP (or other AI platforms as needed). This role bridges data engineering and applied AI, building retrieval pipelines, fine-tuning LLMs, and embedding GenAI into business workflows. 

Working closely with Data Engineers, Model Development Engineers, and MLOps, this role ensures GenAI solutions are secure, scalable, and aligned to enterprise standards while enabling rapid adoption across product domains. 

 

 

A Typical Day

 

GenAI Solution Engineering 

  • Develop and optimize generative AI applications (e.g., copilots, search assistants, summarization tools). 
  • Implement retrieval-augmented generation (RAG) pipelines using enterprise data sources. 
  • Fine-tune LLMs (Vertex AI, OpenAI, Anthropic, LLaMA) for Parts Town–specific use cases. 

Data & Pipeline Enablement 

  • Build pipelines to structure unstructured data (manuals, product catalogs, customer tickets). 
  • Create embeddings and manage vector databases (BigQuery Vector, Pinecone, Weaviate, ChromaDB). 
  • Partner with Data Engineers to ensure AI-ready data assets are available and governed. 

Integration & Deployment 

  • Work with MLOps to deploy GenAI solutions into production with monitoring, retraining, and drift detection. 
  • Develop APIs and microservices for embedding AI into ERP, Salesforce, eCommerce, WMS/Ops, and customer service apps. 
  • Ensure solutions are performant and aligned with enterprise integration frameworks. 

Responsible AI & Governance 

  • Apply guardrails to mitigate hallucinations, bias, and data leakage. 
  • Ensure compliance with Parts Town’s AI governance framework and data privacy regulations (GDPR, CCPA, EU AI Act). 
  • Partner with the AI Council to align GenAI use cases with enterprise priorities. 

Innovation & Enablement 

  • Evaluate emerging tools (LangChain, LlamaIndex, Vertex AI GenAI stack) and recommend adoption. 
  • Build reusable components (prompt templates, connectors, orchestration patterns) to accelerate adoption across teams. 
  • Share best practices and mentor peers on GenAI engineering approaches. 

 

To Land This Opportunity

 

  • You have 5+ years in Data Engineering, AI/ML Engineering, or related roles, with direct experience in generative AI. 
  • You’re proficient in Python, SQL (JavaScript/Node.js a plus). 
  • You have experience with LLMs (training, fine-tuning, embeddings, RAG pipelines). 
  • You obtain hands-on with GCP (Vertex AI, BigQuery, Cloud Run, GKE) and/or other GenAI platforms (OpenAI, Anthropic, Hugging Face). 
  • You’re familiar with vector databases and semantic search. 
  • You understand MLOps practices for deploying and monitoring GenAI solutions. 
  • You hold strong collaboration and communication skills to partner with Product, Engineering, and Business teams. 
  • You have a bachelor’s degree in computer science, data engineering, or related field. Will also accept candidates with proven experience outside of degree. 

 

 

About Your Future Team

We are about working hard and playing hard. We are about having each others back, taking on responsibility and making things better for all. We are gritty, roll back your sleeves and get the job done with an inclusive, positive can-do attitude. We enjoy our social events, celebrating with food (of course) and celebrating our team members life’s milestones and events.

At Parts Town, we value transparency and are committed to ensuring our team members feel appreciated and supported.   We prioritize our positive workplace culture where collaboration, growth, and work-life balance are celebrated. The salary range for this role is $107,815.50 – 137,045.48 salary which is based on including but not limited to qualifications, experience, and geographical location. Parts Town is a pay for performance-company. In addition to base pay, some roles offer a profit-sharing program, and an annual bonus depending on the role. Our comprehensive benefits package includes health, dental and vision insurance, 401(k) with match, employee assistance programs, paid time off, paid sick time off, paid holidays, paid parental leave, and professional development opportunities.

 

Parts Town welcomes diversity and as an equal opportunity employer all qualified applicants will be considered regardless of race, religion, color, national origin, sex, age, sexual orientation, gender identity, disability or protected veteran status.