AI​/Data Engineer

Overview

AI/Data Engineer – Core Role at Wicked File

Location: Remote.

Employment Type: Full-Time.

Experience Level: Mid-to-Senior.

Industry: Automotive SaaS, AI-Driven Analytics.

Wicked File is on a mission to redefine how automotive repair shops understand and act on their financial and operational data. We're turning messy, inconsistent data into insight that drives real-world results. Our platform leverages LLMs and AI to surface trends, identify outliers, and spot the invisible patterns that matter most to shop owners and multi-location operators.

We’re looking for a hands-on AI/Data Engineer who’s ready to take the lead on all things LLM + data processing. This is a mission-critical seat on a lean, fast-moving, highly technical team. You’ll work directly with leadership to build, deploy, and scale the systems that make Wicked File work.

• Interface with remote LLMs (OpenAI, Anthropic, Claude, Gemini, etc.) for document parsing, semantic matching, and complex reasoning tasks.
• Deploy and fine-tune local LLMs (Llama, Mistral, etc.) for specialized tasks where latency, privacy, or cost demands it.
• Train custom LLMs on proprietary datasets to increase task accuracy and context awareness.
• Build and maintain robust data pipelines to clean, standardize, and normalize messy vendor and financial data from dozens of disparate systems.
• Design prompt engineering strategies and feedback loops to improve reliability and accuracy of model outputs.
• Work in AWS to deploy scalable and cost-efficient services across EC2, Lambda, S3, ECS, etc.
• Own your output – From prototype to production, you’ll be expected to think in terms of performance, security, cost, and maintainability.

• Proven experience working with LLMs via API (OpenAI, Claude, Gemini, etc.) and fine-tuning or training smaller models (e.g. Llama, Mistral, etc.).
• Strong background in Python or Node.js
  , including working with libraries like Lang Chain, Transformers, or similar.
• Deep understanding of data wrangling, cleansing, and normalization techniques across unstructured and semi-structured datasets.
• Comfortable with AWS – deploying inference pipelines, managing scalable workloads, and optimizing compute/storage costs.
• Knowledge of prompt engineering techniques, context management, and token budgeting.
• Bonus:
  Familiarity with automotive service or financial data
  , or experience parsing documents like invoices/statements.

• Massive Impact – Your work will directly improve business decisions at real shops across North America.
• High Ownership – No silos. You’ll have autonomy and a voice in shaping core tech and product direction.
• Ground Floor – Be part of something early. We’re small, nimble, and moving fast.
• Real-World AI – Not a research role. We’re shipping LLM-powered features used in production by paying customers.

Ready to build something that actually matters? Send us your resume, Git Hub, or a few words about what you've built. Let’s talk.