Member of Technical Staff, Infrastructure

About Obvious

We're building an AI-native workspace—an operating system for work that puts co-intelligence at the center. Start with data or an idea, describe your goal, and Obvious goes to work: running analysis, searching the web, writing documents, generating tables, designing presentations, visualizing data, building dashboards, and more.

As Steve Jobs imagined the personal computer as a bicycle for the mind, Obvious imagines AI as a garden for the mind. Less mechanical acceleration. More organic cultivation.

What if, instead of just vibe coding, you could vibe-work? What if getting from idea to done wasn't so opaque, stubborn, and high-latency?

What if there was a way to consistently deliver work that feels like it came from the best version of you on your best day?

That's Obvious.

Why we're hiring for this role

We're not looking for the traditional IT-professional profile—someone who knows Linux, box configuration, and enterprise DevOps but hasn't rethought infrastructure for the AI era. We're looking for an engineer who has spent their career treating infrastructure as the product itself, and who brings that lens to building AI-native infrastructure tooling.

That means owning the systems that make every Obvious engineer, and every Obvious agent, more productive: build and deploy pipelines where rolling back and forth is trivial, model-serving and inference infrastructure that holds up under real AI workloads, and the observability to know what's actually happening in a system that's non-deterministic by nature.

We are small and talent-dense. Among our founding team, we have world-class builders, former founders, and leaders from companies like Netflix, Google, Uber, Meta, Dropbox, Instacart, Shopify, Apple, Datadog, and Twitter (X). If you're excited to build infrastructure that enables others—human and agent—to do their best work, join us.

In this role you will:

• Make deployments boring (in the best way possible)

• Own CI/CD pipelines: optimize build times, improve caching, reduce flakiness

• Evolve our Kubernetes (EKS) deployment strategy for reliability and speed

• Build and harden the infrastructure behind model serving, inference, and agent tooling—not just the app layer around them

• Extend our telemetry with better instrumentation, smarter sampling, and actionable dashboards, including eval pipelines and LLM-ops guardrails

• Build alerting that catches actual problems and ignores noise

• Make the feedback loop from code to production as fast as possible

• Improve preview environments, local dev tooling, and testing infrastructure

• Eliminate toil through thoughtful automation, not another dashboard nobody reads

• Be the engineer who makes other engineers—and agents—faster

You will thrive in this role if you have:

• Come from a company where infrastructure was the product itself—not infrastructure work done in service of someone else's product. Think platforms like Vercel, Railway, Fly.io, Render, Heroku, Netlify, Supabase, Modal, or similar—ideally as an early hire or in a role with real ownership

• Applied that infra background specifically to AI/LLM workloads: model serving, inference infrastructure, agent tooling, eval pipelines, or LLM-ops guardrails—working at an "AI company" alone doesn't count if the infra work itself doesn't show this lens

• Real technical depth in distributed systems: Rust or Go, storage engines, control planes, Ceph, RDMA, eBPF, bare-metal automation, or Kubernetes internals (not just usage)

• A proven record of exceptional achievements and impact

• Strong Terraform skills—you've managed real infrastructure as code

• Hands-on experience with observability tools: OpenTelemetry, Datadog, Dash0, Braintrust, distributed tracing, metrics, structured logging

• You've been on-call, and you've built systems that made on-call better

• You think like a product manager for internal tools, where the product is developer (and agent) productivity

• Willingness to work hard, move fast, and grow quickly in a rapidly changing environment

• A humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed

Nice to have:

• A personal or self-directed infra track record: side projects, homelabs, open-source infra tooling, published writing or talks—signal of genuine intrinsic interest, not just job history

• Security chops: IAM, zero-trust, secrets management

• SRE practices: SLOs, SLIs, error budgets, chaos engineering

• Cost optimization for cloud infrastructure

• Based in Atlanta (nice to have, not required)

• You love the talk "Simple Made Easy"

This role may not be a fit if:

• Your primary identity is enterprise IT or sysadmin work—help desk, Windows/Linux administration, or network admin

• Your DevOps experience is Terraform/Kubernetes/CI-CD done in service of a product company (fintech, healthtech, e-commerce, SaaS) rather than infrastructure as the product itself

• You're a pure database-administration specialist looking for that exact scope—valuable work, but a narrower role than this one

• You don't think developer experience is a first-class concern

• You require highly structured requirements and aren't comfortable with ambiguity

• You're uncomfortable with the pace and changing priorities of a startup environment

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