Hamilton AI Logo

Hamilton AI

Staff Infrastructure Engineer

Reposted 7 Days Ago
Be an Early Applicant
Hybrid
San Francisco, CA, USA
180K-220K Annually
Senior level
Hybrid
San Francisco, CA, USA
180K-220K Annually
Senior level
This role involves owning Hamilton's infrastructure, CI/CD pipelines, and internal platforms while also ensuring safe and efficient AI-accelerated development. Responsibilities include architecting systems for reliability, performance, and compliance in aviation operations, and integrating AI tools into workflows, with a focus on scalability and operational risk management.
The summary above was generated by AI
This role is infrastructure-first, with a second gear in backend or QA.

Hamilton is building the operating system for charter aviation. Quoting, trip planning, live operations, payments, safety-critical data, and sensitive customer information. The software that runs aviation operations doesn't get to be "mostly working." When our systems ship, they need to be correct, observable, and resilient. That's your job.

We're hiring a Staff Infrastructure Engineer infra and internal platforms that let Hamilton's engineering team ship fast without breaking things that matter. Your primary skillset is infrastructure: CI/CD, deployment systems, runtime environments, observability, and developer tooling. Your secondary skillset and the thing that makes you dangerous is depth in either backend engineering or quality engineering. You don't need both. You need one, and you need it to be real.

Now is a pivotal time in how software gets built. AI-accelerated development is not a buzzword here, it's how we operate. Our engineers ship with AI coding agents, and the platform layer is what makes that safe. You will build the CI/CD pipelines, quality gates, automated verification loops, and deployment guardrails that let a small team move at a speed that shouldn't be possible. The better your platform, the more leverage AI gives us. This is how we compound.

What winning looks like in this role

Your first job is to own infrastructure. You will architect and operate Hamilton's CI/CD pipelines, build systems, deployment workflows, and runtime environments. You'll build the abstractions that standardize how services are built, tested, deployed, and observed. Release infrastructure, rollback strategies, production validation. These are yours to own.

Your second job is to make AI-accelerated development safe and fast. As AI agents produce more of our code, the platform becomes the immune system. You'll build the automated verification loops, quality signals, and guardrails that let us trust agent-generated output at production scale. You'll shape how we integrate AI tooling into our development workflow, not as an experiment, but as core infrastructure.

Your third job depends on your secondary skillset. If your background is backend: you'll partner deeply on API design, service architecture, and infrastructure patterns that scale with complexity. If your background is QA: you'll build the automation frameworks, testing infrastructure, and release-blocking quality gates that become core platform.

Finally, you will shape the long-term platform roadmap aligned with enterprise and regulatory requirements in aviation. A domain where rigor is non-negotiable and your platform decisions scale across the entire company.

The context ("Why Hamilton, why now?")

Charter aviation is a $30B+ market running on phone calls, spreadsheets, and legacy systems stitched-together. This is a 24/7 industry where brokers, operators, and crews are constantly on call. A single trip touches pricing logic, aircraft availability, crew scheduling, regulatory compliance, payment processing, real-time operational data, and the list goes on. When something breaks, someone either loses sleep or the entire business loses trust and revenue.
There’s no single platform that solves all these. Teams Frankenstein together tools that were never designed for private aviation. Spreadsheets for quoting, WhatsApp threads for comms, Quickbooks duct-taped to Stripe for payments, and disconnected scheduling software to run aircraft ops. The amount of context-dependent workflows and manual reconciliation creates operational risk. We’re replacing all of it with a vertically integrated system, and soon, a modern banking layer that’s built specifically for how the industry actually runs.
Our customers manage safety-critical workflows and sensitive PII. “Move fast and break things” doesn’t work here. Move fast and break nothing does.
We’re at an inflection point nearing our Series A. We have a small and senior team, using AI-accelerated workflows to punch above our weight. We’ve built a strong foundation by deploying containerized services, typed APIs, and a pattern-driven codebase. But we need someone to take full ownership of the platform layer. Someone who can take what exists, make it better, and continue building as we scale. If you want a place where your infra decisions are felt across the entire company, and you can see the direct impact of your work, this is it!

Who thrives in this role

You've probably been the person other engineers go to when the build is broken, deploys are scary, or nobody can figure out why production differs from staging. You've built CI/CD pipelines that teams actually trust. You're excited about AI changing how code gets written, and you want to build the systems that make it safe.

You non-negotiably:

  • Own problems end-to-end and don't wait for a spec

  • Think in systems and tradeoffs, not tasks

  • Prize reliability in environments where failure is expensive

  • Communicate clearly across engineering, product, and leadership

  • Believe great platform work makes fast shipping possible — not a tax on it

You'll hopefully have experience with some or all of: CI/CD and build systems, containerized runtimes, observability and monitoring, API design, automation frameworks, cloud infrastructure (AWS/GCP), Node.js/TypeScript, and AI-assisted development workflows. Aviation or regulated-domain experience is a bonus. These are things we know you can learn.

The hiring process

Intro call: Get the download from our recruiting team to make sure this is an opportunity that you'll be excited about. We'll want to hear about your motivations and the hardest infrastructure problem you've solved.

Head of Product: Deep dive into your previous roles and projects highlighting those experiences relevant for this role at Hamilton.

Live coding & technical chat: Live coding using code pad and a technical discussion about your solution.

Onsite: Meet the team, work through a realistic scenario, and see how we operate. Coffee is on us.

We move fast and respect your time. If this resonates, we'd be lucky to meet you.

Hamilton is an equal opportunity employer. We cannot sponsor new visas but will support transfers.

HQ

Hamilton AI San Francisco, California, USA Office

501 2nd St, San Francisco, California, United States, 94107 1469

Similar Jobs

2 Days Ago
Hybrid
Mountain View, CA, USA
Junior
Junior
Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
Design, build, and operate large-scale agentic search infrastructure: indexing engines, hybrid sparse/semantic indices, ingestion and enrichment pipelines, entity resolution/knowledge graph, multi-modal retrieval, and production reliability for low-latency agentic search.
Top Skills: ElasticsearchEmbeddingsKnowledge GraphLuceneMulti-Modal IndexingNext-Token PredictionOpensearchSolrVector DatabasesVector Quantization
5 Days Ago
Remote or Hybrid
2 Locations
185K-335K Annually
Senior level
185K-335K Annually
Senior level
Automotive • Big Data • Information Technology • Robotics • Software • Transportation • Manufacturing
Lead design and development of scalable, high-performance ML training infrastructure. Drive distributed training performance optimization, observability, and developer experience. Own cross-functional infrastructure initiatives, set technical direction and standards, and mentor engineers to deliver platform capabilities that support large-scale model training.
Top Skills: AWSAzureDistributed TrainingFsdpGCPGpu ComputingPipeline ParallelismPythonPytorch 2.XTensorFlow
9 Days Ago
In-Office or Remote
2 Locations
188K-275K Annually
Senior level
188K-275K Annually
Senior level
Cloud • Information Technology • Machine Learning
The Staff Software Engineer will design and implement the backend architecture for Marimo's molab, focusing on high availability, low latency, and system stability, while utilizing CoreWeave's infrastructure.
Top Skills: Cloud InfrastructureDistributed SystemsGpu Resource AllocationKubernetesPython

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account