Artificial Intelligence (AI) Analyst

Factory Motor Parts Careers•Eagan, MN

1d•Onsite

About The Position

Factory Motor Parts is moving its AI and data platform past reporting and into production systems: retrieval over unstructured company documents, agents that query live business data, and automations that push AI output into daily operations. The AI Analyst builds and supports those systems end to end - retrieval pipelines, the agent and tool layer, the data models underneath them, and the evaluation and monitoring that keep the output trustworthy enough for people to act on. This is a hands on, build focused role on a small team with wide scope. The right person writes Python and SQL comfortably, thinks clearly about how data is modeled, and iterates fast on systems where correctness matters more than novelty.

Requirements

Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related technical field
2+ years of hands-on experience in software, data, or AI engineering
Strong Python and strong SQL
Working experience with LLM APIs, prompt design, and structured outputs
Demonstrated experience building a RAG pipeline end to end, including embeddings, vector search, and retrieval evaluation
Solid understanding of relational data modeling, joins, and query performance
Experience integrating systems through REST APIs and webhooks
Version control and basic software engineering discipline, including code review and testing
Clear written communication and the ability to explain technical tradeoffs to non-technical stakeholders

Nice To Haves

Vector databases such as Pinecone, Weaviate, or Qdrant
Agent frameworks and orchestration: LangGraph, LangChain, LlamaIndex, or the Claude Agent SDK
Model Context Protocol (MCP) and tool design for agent access to internal systems
dbt for transformation, testing, documentation, and lineage
Cloud data platform experience — Snowflake, AWS, or GCP preferred
Workflow automation experience, n8n preferred (or Make, Zapier, Airflow)
LLM evaluation and observability tooling such as RAGAS, Langfuse, or LangSmith

Responsibilities

Design, build, and maintain RAG pipelines over FMP's internal documents - chunking, embedding, indexing, and hybrid retrieval - and continuously improve retrieval quality against measured baselines
Develop agent workflows and MCP tools that give AI governed, secure access to live FMP business data, including text-to-SQL against the analytics warehouse
Build and maintain ELT pipelines and dbt models that land and curate data in FMP's data lake for both analytics and AI consumption
Build and maintain production automations (n8n) that connect AI output to daily processes across finance, operations, sales, and warehouse teams
Build evaluation frameworks, monitoring, and cost controls so AI output is measured and trustworthy before it reaches users
Partner directly with Merchandising, Pricing, Finance, Operations, HR, and Legal to turn business problems into working systems, including teams new to AI tooling