Agentic Operations Engineer

Integrate•Seattle, WA

7d•Onsite

About The Position

We're hiring an Agentic Operations Engineer to help us build the internal intelligence operating system of Integrate. This role sits at the intersection of engineering, product, and operations. Your prime directive is to leverage modern AI tooling and agentic strategies to increase organizational velocity across engineering, product, design, and ops. You are an engineer first. You've shipped real full-stack applications, and you understand the discipline of deploying and maintaining software people actually depend on. But what energizes you most is the next layer up: how do we structure a codebase, an organization, and a workflow so that humans and agents can collaborate fluidly? How do we eliminate the scavenger hunt for context and keep that context fresh? This is your purview. This role is part tactical and part strategic. Tactically, you'll write code, build internal tools, automate pipelines and workflows, and audit repos so that the agents working alongside us route correctly and produce high-quality output. Strategically, you'll look ahead, parse requests coming in from product, engineering, design, and ops, and merge them into efforts that make sure we aren't doing redundant or parallel work across teams. You'll audit teams, unblock bottlenecks, stand up new systems, and ship tools that compound across the org. You'll report directly to the VP of Product and work closely with engineering, product, and operations. This role is in person at our Ballard office in Seattle.

Requirements

3–5 years of full-stack engineering experience shipping real production software — not just tinkering
Active, hands-on use of modern AI tooling — Cursor, Claude Code, Codex, agent frameworks, MCP, and whatever shipped this week
Comfort with prompting, eval design, and integrating LLMs into production code paths
Experience building developer-facing tooling: CLIs, internal chatbots, small web apps, automation scripts — bonus if you can point to them
DevOps fundamentals — Docker, CI/CD pipelines (GitHub Actions or similar), deploy and maintain internal tools without supervision
Security fundamentals — authn/authz, secret management, API surface design, and a working sense for what's safe to expose internally vs. externally
Comfort with Python and a typed language (Go and/or TypeScript)
US person status (including US citizens, U.S. permanent residents, individuals granted U.S. asylum status, or individuals admitted in U.S. refugee status) is a required qualification for this position.

Nice To Haves

You don't need to be senior. If you spend your nights shipping side projects on the bleeding edge of AI tooling, that signal matters more than years on a resume

Responsibilities

Build the internal "intelligence OS" of Integrate — the tools, agents, automations, and conventions that compound the team's productivity over time
Organize our repos, docs, and conventions so that AI coding agents route correctly, find the right context, and produce high-quality output
Stand up and maintain internal tooling — chatbots employees use to find answers, CLI tools that support day-to-day workflows, small web apps that smooth over operational friction
Build and own automations around the PR review process — code quality checks, agent-driven first-pass review, security and convention enforcement
Partner with engineering to identify code-quality issues, ambiguous structures, or stale conventions that slow down both humans and agents, and propose fixes
Support the product team as they get closer to the codebase, and the design team as they work more directly in feature branches — pairing, building scaffolding, refining prompting workflows
Evaluate, deploy, and govern bleeding-edge AI tooling: IDE agents, evals, model gateways, MCP servers, on-prem systems
Audit teams proactively. Surface friction. Propose system-level fixes rather than one-off patches
Be the person teammates come to with questions, ideas, and half-built experiments — and the person who leads when no one is asking
Plan three to six months ahead for what an AI-native Integrate looks like, including on-prem and locally-run agent infrastructure for our most security-sensitive workflows
Contribute occasionally directly to the core application codebase when needed