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MaintainX is the world's leading AI-powered maintenance and asset management platform, serving 14,000+ customers including Duracell, Shell, Cintas, and Brenntag. We raised $150M in Series D funding led by Bessemer Venture Partners and Bain Capital Ventures, bringing our total funding to $254M. We were named to the Forbes 2025 Cloud 100 , the definitive ranking of the top 100 private cloud companies in the world. We're growing fast and hiring the talent to match. 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 What’s In It For You Competitive salary and meaningful equity opportunities. Healthcare, dental, and vision coverage. 401(k) / RRSP enrollment program. Take what you need PTO. A Work Culture where: You’ll work alongside folks across the globe that reflect the MaintainX values: Smart Humble Optimists. We believe in meritocracy, where ideas and effort are publicly celebrated. Our mission is to deliver one platform for maintenance, repair & operations teams to keep the physical world running. We believe the greatest asset in any organization is the people. That’s why we built an intuitive, mobile-first solution to help boost productivity and collaboration across teams and locations. MaintainX is committed to creating a diverse environment. All qualified applicants will receive consideration for employment without regard to race, colour, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.