Senior DevOps / Infrastructure Engineer

We’re looking for a Senior DevOps / Infrastructure Engineer to operate the infrastructure behind Monad, and to push how much of that operation can be driven by AI. You’ll keep our globally-distributed validator, full node, and archive fleet healthy across mainnet and testnet, own our infrastructure-as-code and observability, and build the agentic tooling and guardrails that let a small team safely operate a large fleet. As more of our engineering shifts toward AI, this role is central to designing the workflows, deterministic guardrails, and security perimeters within which autonomous agents operate our infrastructure; you’ll also help stand up and operate the infrastructure behind our own growing model workloads., * Operate the Monad node fleet: health, sync, upgrades, and recovery across validators, full nodes, archive/historical, and indexer nodes on mainnet and testnet, including safe, staged rollouts and incident response.

• Own our infrastructure-as-code: Ansible for fleet configuration, Terraform + Atlantis for cloud and DNS, and Kubernetes/Flux (GitOps) for platform services.
• Build and operate observability and alerting (Prometheus, Grafana, Loki); create dashboards and alerts that catch problems before they page while minimizing false positives.
• Automate the release pipeline: node upgrades, canary rollouts, snapshot/restore, and the guardrails that bound blast radius (e.g., protecting validators from automated changes).
• Design and build agentic operations: develop AI agents, tooling (e.g., MCP servers), and runbooks-as-code that let agents safely investigate, diagnose, and execute routine operations, with deterministic guardrails and human oversight.
• Codify operational knowledge into tools and automation that the whole team, and its agents, can reuse.
• Harden nodes and services, manage secrets, and continuously drive down manual toil.

• You have 5+ years in DevOps, SRE, or Infrastructure Engineering, operating production systems at scale.
• You have strong Linux, systemd, networking, and shell fundamentals, and you’re comfortable debugging live systems over SSH.
• You have deep, hands-on infrastructure-as-code experience with Ansible and Terraform.
• You have experience with observability stacks (Prometheus, Grafana, Loki, or equivalents).
• You have hands-on fluency with AI-assisted engineering: you use coding agents and LLM tooling in your daily workflow and have judgment on where it helps and where it’s risky.
• You have experience designing automation with safe guardrails, and you bring calm, methodical incident response.
• You have programming and scripting experience (e.g., Python, bash).
• Experience with Kubernetes and GitOps (Flux or Argo) is a plus.
• Experience building AI agent tooling, MCP servers, or agent orchestration frameworks is a plus.
• Experience serving inference, either locally or as a service is a plus.
• Previous experience with blockchain clients or node operations is a plus.
• A Bachelor of Science in Computer Science, Engineering, or a related field is a plus.

Pulled from the full job description

• Paid parental leave
• Parental leave
• Health insurance
• 401(k) matching
• Paid time off
• Vision insurance
• Health savings account, * Huge opportunity: The Ethereum Virtual Machine (EVM) standard is ubiquitous, but existing EVM-compatible chains are very slow. Monad’s core innovations offer developers the best of both worlds (portability and performance) and are a game-changer for mass user adoption in crypto.
• The right team: You’ll be part of a small, exceptional team (engineers and researchers make up 90% of the team).
• Open by default: Our core software is public on GitHub. You’ll build in the open, and your work ships where the whole ecosystem can see it.
• Culture: We’re a lean team working together to achieve very ambitious goals. We are united in our culture of collaboration, low ego, and high-quality output. As an early member of our team, you’ll help to shape our culture.
• Compensation: You’ll receive a competitive salary and equity package.
• Resources and growth: We’re well-capitalized, with backing from leading venture funds like Paradigm, Electric Capital, Greenoaks, Dragonfly, and Coinbase Ventures. We keep a lean team, and this is a rare opportunity to join. You’ll learn a lot and grow as our company scales., The base salary range for this role is $180,000 - $250,000. This reflects the minimum and maximum range across US locations. It does not include benefits, token, or equity incentives. The final offer may vary based on factors such as relevant skills, experience, domain expertise, and work location. If you are based outside of the US, we have geographic considerations that may impact your final compensation.

Benefits for all Full-Time Employees:

• Private health insurance options
• Flexible paid time off
• Monthly wellness reimbursement
• Paid parental leave

Benefits for US employees:

• World-class benefits package with 100% paid medical, dental, and vision insurance including 75% coverage for dependents and HSA + FSA options
• 401(k) with company match
• Lunch and dinner stipend (in-office NYC)

Benefits for employees hired through an EOR (outside of the US) will be based on EOR offerings and country-specific requirements.

Category Labs is an Equal Employment Opportunity (EEO) employer and welcomes all qualified applicants. Applicants will receive fair and impartial consideration without regard to race, sex, color, religion, national origin, age, disability, veteran status, genetic data, or other legally protected status.

Compensation Range: $180K - $250K

We’re an AI-native team, and we expect engineers to use coding agents and keep up as the tooling evolves. A few things we believe:

• AI is leverage, not a crutch. Review what it generates with the same scrutiny you’d give a teammate’s PR, and own every line you ship.
• Judgment is what matters, not how long you typed by hand. We won’t ask for “N years of [tool].” The stack turns over every few months, so what matters is that you pick up new tools fast and know where and when they apply.