Platform Engineer (DevOps)

Mine Vision Systems is a mining technology company building the decision-making platform for underground mining. We introduce high-fidelity data into the mining workflow that has simply never existed before, enabling operators to move from assumptions to evidence-based decisions. Our digital infrastructure is designed to map, monitor, and manage the underground mining environment with confidence, creating a persistent, data-rich foundation for operational and strategic decision-making. Since the launch of our flagship product, FaceCapture, in late 2023, adoption has accelerated rapidly as customers realize the value of truly understanding their underground operations.

We focus on underground mining of critical minerals and precious metals, where small improvements in accuracy and insight drive outsized returns. Our technology delivers millions of dollars in annual value by minimizing overbreak, improving ore calls, enhancing resource models, and enabling a growing set of high-impact applications across the mine lifecycle. By transforming raw underground data into actionable intelligence, Mine Vision Systems empowers mining teams to operate more efficiently, more predictably, and with greater confidence than ever before.

Role Summary 

We are looking for an AI Platform Engineer (think AI-forward devops++) to own the engineering platform that empowers MVS to rapidly ship safe, high-quality software faster. You will partner with our existing CI/CD lead to take our CI/CD pipeline from “working” to fully automated, and you will own the build-out of ContextOps, our internal platform that keeps engineering context up to date and AI-tool-ready so we can use AI at scale. Over time, your scope can expand to include ownership of AWS infrastructure. This role is platform-heavy and AI-forward; it prioritizes durable automation, judgment about where to invest engineering effort, and a track record of using AI as a daily multiplier. The right person treats developer experience as a product and the platform as something engineers reach for, not around.

Key Responsibilities

• CI/CD automation: Partner with our existing CI/CD lead to evolve our CI/CD pipeline (GitHub Actions, Rulesets, CodeRabbit, pre-commit hooks) toward fully automated build, test, security scanning, and release — including merge queue, mutation testing, DORA reporting, and immutable CI audit logs.
• ContextOps ownership: Own and operate the engineering context platform, code-adjacent Markdown context (Context Driven Development), the non-codebase AI knowledge repo, read-only Google Docs ingestion, context-drift CI enforcement, and CODEOWNERS gates for top-level architecture context.
• AI-assisted developer experience: Maintain and improve the day-to-day tools engineers use with AI — Claude Code, CodeRabbit, AI PR review, opt-in git hooks, context-sync helpers. Treat developer productivity as a product.
• Security and compliance built in: Embed security and SOC 2-relevant controls into the pipeline — secret scanning, dependency scanning, SBOM, license compliance, signed artifacts.
• Observability and reliability: Build the logging, metrics, alerting, and runbooks that let a small team operate cloud services with confidence.
• AWS infrastructure (growing scope): Over time, partner with our IT lead on AWS, Organizations, SCPs, IAM Identity Center, KMS, backup posture, and eventually own select areas as the platform scope expands.
• Internal tooling and automation: Author and own internal CLI helpers, GitHub Actions, and services that automate repetitive engineering work.
• Documentation and runbooks: Maintain runbooks, incident response, and post-incident learning loops; document the platform to enable engineers to self-serve. 

Qualifications

• 3+ years of professional experience in DevOps, Platform Engineering, Site Reliability Engineering, or a similar engineering-platform role.
• Strong hands-on CI/CD experience — GitHub Actions, build pipelines, test orchestration, release automation.
• Fluent with cloud platforms (AWS preferred), infrastructure-as-code (Terraform or equivalent), and container workflows (Docker; Kubernetes a plus).
• Hands-on, demonstrable use of AI tools (Claude Code CLI, CodeX, etc.) as a daily multiplier in your own work. You will be expected to demonstrate this directly in the interview process.
• Comfortable with Linux/Unix systems and scripting (Python and Bash).
• Experience with observability tooling (Prometheus / Grafana / ELK or equivalent).
• Bias toward systems thinking, durable automation, and “make it self-serve” over one-off heroics.
• Strong written communication — you will author runbooks, context docs, and proposals that engineers and executives both read.

Desirable

• Background in robotics, embedded, or industrial systems environments.
• Experience with AWS Organizations / Control Tower, IAM Identity Center, KMS, and SOC 2 / ISO 27001 controls.
• Familiarity with Markdown-based context systems (Context Driven Development, Anthropic Skills, AGENTS.md) or building developer-facing AI tooling.

What Success Looks Like

• CI/CD reaches autopilot. The pipeline runs without engineer babysitting; merges are confident; release frequency goes up while incidents go down.
• ContextOps is a platform, not a project. Engineers find current, accurate context where and when they need it; new hires ramp on AI-assisted workflows from day one.
• Developer experience is a force multiplier. Engineers report, and metrics confirm, measurable productivity gains from the AI-assisted tooling you maintain.
• AWS posture quietly improves. As scope expands, you take meaningful AWS infrastructure ownership and the team feels safer, not more bottlenecked.
• You are visibly AI-forward. Your own workflow models what you build; teammates adopt practices because you have demonstrated them.

Benefits

• We are a fast paced and growing company with real robotic hardware in the field around the world, generating actual revenue
• Competitive compensation and full benefits: medical, dental, vision, disability, life insurance, 401(k) with match
• Uncounted PTO policy and flexible hybrid work model
• Small, fast-moving team with hands-on work and immediate impact

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