Applied AI Engineer
- Location
- San Francisco, CA (Remote) · Hybrid
- Job type
- Full-time
- Level
- Senior
- Listed
- Today
Skills & highlights for this role
- prompt engineering
- structured output
- tool-use
- RAG
- retrieval-context patterns
- eval dataset design
- rubric design
- factuality/relevance/quality measurement
- production LLM feature deployment
- multimodal input processing (video, PDF, audio, image)
Also useful
- LLM observability
- cost awareness
- eval platform experience
- document understanding
- video understanding
- OCR
- retrieval systems
- fine-tuning
The Role
You'll own the Generation half of Document Intelligence: turning multimodal primitives (keyframes, transcripts, OCR) into schema-valid entities like SOPs, and holding the line on quality so "fast" never becomes "fast and wrong."
- Design and iterate recipe prompts — system, few-shot, and context assembly — for each generation recipe
- Define per-entity target schemas and domain validators (procedure step-type rules, field caps) that generated output has to pass
- Build generation-quality eval datasets and rubrics, offline and online, running on LLMX's eval pipeline, and close the loop when quality regresses
- Assemble multimodal context windows from keyframes, transcript, and OCR so each model call has exactly what it needs
- Choose the model and token budget per recipe based on quality, cost, and latency tradeoffs
You'll ride on LLMX for model access and on Attachments for ingestion, and hand off validated entities to the domains that own them. You'll report to our Engineering Lead and work closely with the Processing side of Document Intelligence.
Minimum Requirements
- Strong applied GenAI craft - prompt engineering, structured output / tool-use, RAG and retrieval-context patterns
- Real eval discipline: you've built datasets and rubrics, measured factuality/relevance/quality, and closed the loop on regressions yourself
- Shipped LLM features into production services, not notebooks, and can connect model performance to product impact
- Comfort working with multimodal inputs - video, PDF, audio, image - converted to text or structured output
Nice to have
- LLM observability / cost awareness, or experience with an eval platform
- Document, PDF, or video understanding; OCR; retrieval systems
- Light fine-tuning experience, or familiarity with the industrial/maintenance domain
Additional information
Our mission is to keep the physical world running. Factories, fleets, hospitals and campuses stay up because the people who maintain them have tools worth using. That is what we build.
Pay and benefits
Compensation and benefits. Base pay is one part of the package. Depending on the role, compensation may also include commission, an annual bonus and equity. Benefits differ by country.
Belonging. We take pride in a culture where everyone can thrive.
About Maintainx
MaintainX is a leading mobile-first work execution platform for industrial and frontline teams. More than 15,000 customers, including McDonalds, Michaels, Cintas, Redimix, and U.S. LBM, use MaintainX to cut unplanned downtime and run better operations, across 16 million managed assets and 92 million completed work orders.
In August 2026 MaintainX became part of Autodesk, joining Autodesk Operations Solutions the organization unifying Autodesk's operations platform alongside Tandem, FlexSim and Fusion Operations. Autodesk's strategy is to converge design, make and operate into one continuous lifecycle: design an asset, build it, run it, then feed what you learn running it back into the next design. Autodesk had design and make. Operate is the phase that tells you what actually happened, and it is ours.
Frontier models are getting commoditized. The operating data underneath them isn't — and that's what we own. 13.9M+ managed assets, 79.5M+ completed work orders, and 150,000+ technicians generating trustworthy operating data every week, at the point of work.
Document Intelligence is the horizontal engine that turns that raw material — any file a customer hands us — into structured, trustworthy maintenance knowledge, and into the AI-native entities and answers built on top of it.
From Maintainx's careers page, first listed on Rolev.ai on November 14, 2026. Rolev.ai is not the employer.
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Common questions
Where is the Applied AI Engineer job at Maintainx located?
Yes, this Applied AI Engineer opening at Maintainx is listed as San Francisco, CA (Remote) (Hybrid). Always check Maintainx's application page for specific state eligibility or relocation policies.
What qualifications are required for Applied AI Engineer at Maintainx?
For the Applied AI Engineer role, Maintainx highlights experience with prompt engineering, structured output, tool-use, RAG, retrieval-context patterns, eval dataset design. Rolev.ai can score your existing resume against these requirements and show any skill gaps before you apply.
How do I apply for the Applied AI Engineer position at Maintainx?
This listing links directly to Maintainx's Ashby application page. You can apply directly on Maintainx's site, or use Rolev.ai to check your resume fit, generate a zero-hallucination tailored resume and cover letter for this posting, and autofill the Ashby application form in 1 click with the Rolev.ai Chrome extension. You always review the form and press Submit yourself.