Mojo Ai

Safety Mojo | Sandy, Utah | Growth Stage Help us transform how an entire industry thinks about safety About Safety Mojo

Mojo AI is revolutionizing safety management in high-risk industries like construction and oil & gas. How are we doing this? With Safety Mojo – our groundbreaking, AI-powered app designed for frontline safety professionals. Right now, we’re at an inflection point . We’ve proven product-market fit, we have incredible customers who love what we’ve built, and we’re moving from startup phase into serious growth mode. The next 18 months are going to prove that we’re the new standard for safety technology. And we need exceptional professionals to help us do that

The Role

We’re looking for an Sr AI Engineer who gets genuinely excited about solving real problems with AI. Not someone who just wants to chase the latest models because they’re new and shiny—we want someone who asks “what will actually make workers safer?” and “what will help safety managers prevent incidents before they happen?”

Thisisn’tdemo work.You’llbe shipping features that construction superintendents use every morning to figure out where they need to be. Features the frontline needs in emergencies. Features that Spanish-speaking crews use to report whatthey’reseeing in their own words. Your work directlyimpactswhether someone goes homesafeat the end of their day.

What you'll actually be doing

Leading our workflow architecture

• We need to migrate our AI workflows to N8N and build somethingthat’sactually robustand scalable, not the patchwork of toolswe’vebeen using
• You’lldesign the workflow orchestration that connects our various AI models, data sources, and business logic in a way that makes sense
• Build workflows that are observable and self-healing, because they need to scale with us as we grow quickly

Making our NLP better

• Our conversational AI lets workers create safety reports just by talking—in English or Spanish.You’lloptimizeand fine-tune that experience
• We have this feature called “Ask Mojo” that turns complex safety manuals into natural conversations. It needs to get better at making sure workers get the right answer from the right document, every time
• Build context-aware understanding that knows the difference between “fall protection” on a 30-story building versus a 6-foot ladder—because that context really matters

Pushing our OCR and computer vision forward

• Our Flex PTP technology extracts structured data from any safety form, whetherit’sa pristine PDF or a mud-stained piece of paper photographed at sunset on a jobsite. We need to make this even better
• Improve accuracy on handwriting recognition, checkbox detection, form field extraction—all acrosswildly inconsistent formats
• Build intelligence thatdoesn’tjust extract text butactually understandswhat it means in a safety context

Collaborating across the team

• Work with product managers to turn user pain points into technical solutions thatactually solveproblems
• Partner with other engineers to make sure your AI models integrate smoothly into the broader platform
• Talk directly to customers sometimes to understand their challenges and make sure whatyou’rebuildingactually worksfor them

What makes you a great fit

You’veactually shippedAI to production

• You know the difference between a modelthat’s95%accuratein testing and an 85%accuratemodel that usersactually trustin the real world
• You’recomfortable across the full stack—from training models to designing APIs to orchestrating workflows
• You write code that other engineers want tomaintain(or at leastdon’thatemaintaining)

You care more about impact thanthe technologyitself

• You get excited about solving a real problem imperfectly rather than building a perfect solution to the wrong problem
• You measure success by what users can do, not just by model metrics
• You’retotally fineusing “boring” technology ifit’sthe right tool for the job

You’rea self-starter who can handle ambiguity

• Youdon’twait around for perfectly specified requirements. You talk to users, figure out the core problem, propose solutions, and execute
• You can make technical decisions with incomplete information and then adjust as you learn moreSomeone can give you a vague goal like “make our OCR work better on handwritten forms” andyou’llturn that into a concrete plan with actual milestones

You obsess over the right details

• You care about latency because a 2-second response time is the difference between a worker using your feature or avoiding it completely
• You think deeply about error handling because a confusing error message on a construction siteisn’tjustannoying—it creates real safety risk
• You design for actual conditions: poor lighting, people wearing gloves, limited connectivity, multilingual users
• You can explain complex technical stuff to product managers, customers, and executives in a way they understand
• You write documentation that helps your teammates understand not just what your code does, but why you built it that way
• You’renot precious aboutyourideas—you care more about being effective than being right

What you need to have

Musthaves

• 3+ years building and deploying AI/ML systems that actually run in production
• Strong Python skills and experience with modern ML frameworks like TensorFlow orPyTorch
• Real NLP experience —whether that’s fine-tuning LLMs, prompt engineering, RAG, or classical NLP approaches
• Hands-on work with computer vision and OCR (OpenCV, Tesseract, modern vision models, document AI services)
• Workflow automation experience with N8N is our primary tool
• Solid software engineering fundamentals : version control, testing, CI/CD, monitoring, observability

Nice to haves

• Experience with document understanding problems—forms, invoices, receipts, scanned documents,that kind of thing
• Multilingual NLP experience, especially the challenges that come with building for Spanish/English bilingual users
• Background in highly regulated industries where accuracy and complianceactually matter(construction, healthcare, finance)
• Experience with mobile-first or field-worker applications where connectivity is spotty and usability constraints are very real
• Open sourcecontributions or side projects that show how you think about problems
• You’vebeen at a growth-stage startup before where you had to wear multiple hats
• API design and integration —you’vebuilt systems that reliably connect multiple services

Why this role is different

The stakes are real. Your workdoesn’tjust move engagement metrics—it prevents injuries. When your OCR accurately extracts a permit, when your NLP correctly understands a hazard report, when your workflow gets critical information to the right person fast enough—real people are safer because of what you built.

You’llhave real ownership. We’resmall enough thatyou’llsee the direct impact of your work.You’lltalk to users.You’llinfluence theproductroadmap.You’llmake architectural decisions that define how we scale over the next few years.

The timing is perfect. We’reat the most exciting phase of a company’s life—we’veproven theconcept,we have product-market fit, and nowwe’rescaling.You’llhelp build the technical foundation for our next stage of growth, andyou’llgrow right along with us.

The problems are genuinely hard. Extracting meaningful structure from unstructured chaos. Understanding natural language in a specialized domain. Building AI that construction workersactually wantto use.You’llhave the autonomy to explorenew approacheswhen they make sense.

The mission matters. Everyone here cares deeply about worker safety. Construction alone accounts for 20% of workplace fatalities.We’vetalked to workerswho’vebeen injured.We’vemet safety managers who feel helpless watching preventable incidents happen. Thisisn’tabstract forus—we’rehere to fix it.

What we offer

• Competitive salary plus meaningful equity in a high-growth company
• Comprehensive health, dental, and vision insurance
• Flexible PTO—we trust you to manage your own time
• Based out of our Sandy, Utah office—combine focused deep work time with valuable in-person collaboration
• Must be local to Greater Salt Lake City area toparticipatein regular office days and team collaboration
• Flexible schedule that balances remote work with intentional time together
• Modern office space in Sandy with all the tools and tech you need
• Collaborative but not meeting-heavy—we default to async communication and respect deep work time

Growth & Impact

• Direct access to leadership and real influence over company direction
• Opportunity to build and eventually lead a team as we scale
• Work on problems that stretch your capabilities and expand what you can do
• See the tangible impact of your work on real users every single day

Ready to build something that actually matters?

If you’re energized by using AI to solve real problems for real people, if you want to worksomewhereyour code has immediate and measurable impact, and if you’re looking for the next phase of your career where you can make a genuine difference—let’s talk.

Pay: $50,000.00 – $100,000.00 per year

• 401(k)
• 401(k) matching
• Health insurance
• Health savings account
• Paid time off
• Vision insurance

Application Question(s):

• Are youlocatedin or around the Salt Lake City, Utah area?