Applied AI Engineer

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.

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

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. 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.