AI/Data Engineer – Core Role at WickedFile
Location: Remote.
Employment Type: Full-Time.
Experience Level: Mid-to-Senior.
Industry: Automotive SaaS, AI-Driven Analytics.
WickedFile 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 WickedFile work.
What You’ll Do:
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Interface with remote LLMs (OpenAI, Anthropic, Claude, Gemini, etc.) for document parsing, semantic matching, and complex reasoning tasks.
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Deploy and fine-tune local LLMs (Llama, Mistral, etc.) for specialized tasks where latency, privacy, or cost demands it.
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Train custom LLMs on proprietary datasets to increase task accuracy and context awareness.
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Build and maintain robust data pipelines to clean, standardize, and normalize messy vendor and financial data from dozens of disparate systems.
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Design prompt engineering strategies and feedback loops to improve reliability and accuracy of model outputs.
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Work in AWS to deploy scalable and cost-efficient services across EC2, Lambda, S3, ECS, etc.
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Own your output – From prototype to production, you’ll be expected to think in terms of performance, security, cost, and maintainability.
What You Should Bring:
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Proven experience working with LLMs via API (OpenAI, Claude, Gemini, etc.) and fine-tuning or training smaller models (e.g. Llama, Mistral, etc.).
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Strong background in Python or Node.js, including working with libraries like LangChain, Transformers, or similar.
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Deep understanding of data wrangling, cleansing, and normalization techniques across unstructured and semi-structured datasets.
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Comfortable with AWS – deploying inference pipelines, managing scalable workloads, and optimizing compute/storage costs.
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Knowledge of prompt engineering techniques, context management, and token budgeting.
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Bonus: Familiarity with automotive service or financial data, or experience parsing documents like invoices/statements.
Why Join WickedFile:
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Massive Impact – Your work will directly improve business decisions at real shops across North America.
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High Ownership – No silos. You’ll have autonomy and a voice in shaping core tech and product direction.
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Ground Floor – Be part of something early. We’re small, nimble, and moving fast.
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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, GitHub, or a few words about what you've built. Let’s talk.
