Software Engineer - New Grad

 Posted 2 months ago
     
0-2 years experience
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AI Summary

You will work alongside senior engineers to build and extend backend services and end-to-end features for active mining operations. You will also contribute to applied AI features, including computer vision pipelines and LLM-based automation.

Company Overview

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 founders started their careers at Palantir before going on to build Blend Labs (publicly traded fintech, founded as CTO) and Even (acquired by Walmart). Our leadership team brings experience from Uber, Metropolis, and other high-bar organizations. We're a small, senior team that ships daily to production mines.

AI isn't just our product — it's how we build. We're an AI-first engineering team that uses the latest models and tooling throughout our development process, moving faster and at higher quality than traditional teams our size.

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.

What You'll Do

You'll work alongside senior engineers on real features that run at active mine sites — not internal tooling or throwaway projects. We expect new grads here to ramp quickly and take on meaningful ownership within their first few months.

  • Build and extend our TypeScript backend serving real-time mining operations data

  • Ship features end-to-end: from database to API to React UI

  • Work on applied AI features using LLMs for intelligent analysis and automation

  • Contribute to computer vision pipelines leveraging AWS Rekognition, TensorFlow, and OpenCV

  • Deploy to production with CI/CD, with increasing ownership over time

  • Interact directly with users and translate real-world operational challenges into features

  • Work closely with our CEO and a senior team invested in making you great

Tech Stack

  • Backend: TypeScript, Node.js, Prisma, PostgreSQL, GraphQL

  • Frontend: TypeScript, React

  • AI/ML: LLMs, AWS Rekognition, TensorFlow, OpenCV

  • Infrastructure: Docker, Kubernetes, DigitalOcean, AWS

What We're Looking For

Must-Have Qualifications

  • BS in Computer Science or a related field (completed or completing in 2025)

  • Strong CS fundamentals — data structures, algorithms, and system design

  • Proficiency with agentic coding tools (Claude Code, Codex, or Cursor) and an AI-first development style

  • Comfort working across the stack

  • Ability to work independently and ramp without heavy hand-holding

  • US citizen or permanent resident, based in the US

Nice-to-Have Qualifications

  • Prior internship experience working on a production codebase

  • Strong TypeScript proficiency

  • AI, computer vision, or ML experience

  • Startup or fast-paced team experience

What You'll Get

  • Competitive salary and equity

  • Real ownership from day one: your code ships to production mines

  • Direct mentorship from a senior team with deep startup and industry experience

  • A front-row seat to building AI infrastructure for a critical global industry

Interview Process

  1. 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, and system design. No trick questions — we're testing how you think about real code.

  2. Live coding interviews (3 x 1-hour sessions) — Algorithmic problem solving and a simulated development tasks.

  3. Behavioral interview with senior leadership — Culture fit, working style, and past experience.

  4. Reference checks

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