Realm builds AI for the mining industry. We integrate with existing mine infrastructure — cameras, SCADA systems, drones, and data repositories — to predict equipment failures, detect unsafe behaviors, and optimize operations. Our platform deploys intelligence in various ways to improve productivity and safety — monitoring PPE compliance via computer vision, optimizing froth flotation processes, analyzing longwall shearer performance, tracking MSHA citation patterns, and more.
Our culture values high agency, deep ownership, collaboration, and autonomy across a fully remote workforce. Teams here move quickly and make meaningful contributions to a product that shapes global industrial outcomes.
Our founders previously built Blend Labs (publicly traded fintech, founded as CTO) and Even (acquired by Walmart), with early careers at Palantir. We're a small, senior team that ships daily to production mines.
Build and extend a TypeScript/GraphQL backend serving real-time mining operations data across web and mobile clients
Work across the stack: backend services (50%), applied AI/ML (25%), React frontend (15%), and infrastructure (10%)
Build computer vision pipelines — integrating services like AWS Rekognition, TensorFlow, and SAM3 for PPE detection, person recognition, and safety monitoring
Integrate with industrial systems (SCADA/OPC-UA) to monitor and optimize mine equipment in real time
Ship features end-to-end: from databases to GraphQL API to React UI
Deploy to production daily via Kubernetes with CI/CD
Work with LLMs (Claude, GPT, Gemini) for intelligent analysis and automation features
Own features in a small team where your code runs at active mine sites
Interact directly with users to deeply understand customer needs. Translate real-world operational challenges into intuitive, high-impact features
Work closely with our CEO — former CTO and cofounder of Blend Labs — to build a world-class engineering organization from the ground up.
Backend: TypeScript, Node.js, Express, GraphQL, Prisma, PostgreSQL, ClickHouse, Rust, Python
Frontend: React, Vite, Tailwind
Mobile: React Native, Expo
AI/ML and Computer Vision: LLMs, AWS Rekognition, TensorFlow, SAM3, OpenCV
Infrastructure: Docker, Kubernetes, Pulumi, GitHub Actions, DigitalOcean, AWS (S3, CloudFront)
Real-time: MQTT, MediaMTX, WebSockets
Experience & Skills
2+ years of professional software engineering experience (high-quality internships included)
Strong coding skills, problem-solving ability, and CS fundamentals (data structures, algorithms, system design)
Comfort working across the stack — you don't need to be an expert in everything, but you're willing to write a React component, debug a Kubernetes pod, or tune a database query as needed
Engineering Judgment & Quality
Great judgment and intuition about security, testing, code quality, and tech debt
Appreciation of continuous delivery, clean code, and automated testing
Ability to design good generalizations while avoiding premature overengineering
Ownership & Independence
Entrepreneurial work ethic, drive for excellence, and belief in meritocracy, personal responsibility, and hard work
Ability to own features end-to-end with minimal direction
Highly independent and able to come up to speed without heavy assistance
Work Style & Collaboration
Experience and comfort working on a remote team
Ability to handle multiple work streams and frequent context switching as priorities change
Flexible work hours (occasional nights and weekends) when necessary to sprint for urgent deliverables
Humility to learn from others while also being able to advocate for and execute on improvements you believe in
Eligibility
US citizen or permanent resident, and based in the US
Startup experience — comfort with ambiguity and wearing multiple hats
Strong TypeScript proficiency
Strong network of top-tier engineers
Familiarity with computer vision or ML inference pipelines
Experience integrating with industrial/IoT systems
Functional programming style preferences (immutability, declarative patterns)
Engineering quiz (async, ~60 min) — A 10-question code reading and analysis assessment. You pick your language (TypeScript, Python, Go, or C++) and answer questions covering code comprehension, bug detection, performance analysis, code review, and system design. No trick questions — we're testing how you think about real code.
Live coding interviews (~3 sessions) — Algorithmic problem solving and simulated development tasks representative of actual work.
Behavioral interview — Culture fit, working style, and past experience.
Reference checks
realmalliance