Applied AI Engineer
About The Position
MaintainX is a leading mobile-first work execution platform for industrial and frontline teams. More than 13,000 customers, including Duracell, McDonald's, Shell, DHL and Volvo, use MaintainX to cut unplanned downtime and run better operations, across 13.9 million managed assets and 79.5 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. 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.
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 Haves
- 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
Responsibilities
- 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
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. For roles in the United States, Autodesk’s benefits are described at benefits.autodesk.com. For roles in Canada and other countries, the plan differs on health coverage, retirement and leave, and your recruiter will walk you through it.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
