Senior Staff DevOps Engineer - Flow

Company Description

It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started.

Join us to put AI to work for people.

Job Description

Flow by ServiceNow is a standalone conversational AI service desk, with its own product and its own codebase. Employees ask for help wherever they already work — Slack, Microsoft Teams, email, or the browser. Flow answers from connected knowledge, handles the request, and runs automations the team publishes. AI is how the product works, and a person stays in control when the action is sensitive.

Flow is a new company inside ServiceNow, reimagining every function from first principles. We hire builders with agency and curiosity who use AI as the default way to design, review, and operate. They challenge inherited ways of working and treat their work as craft.

Flow runs on infrastructure this team owns end to end. You’ll own the AWS platform, the delivery pipeline that puts code on it, the durable-execution plane that runs customer automations in isolation, and the operational surface of an AI runtime — including what it costs and whether it is getting better.

What you get to do in this role

• Own the AWS platform Flow runs on — containerized services, managed PostgreSQL, and an isolated execution plane for customer workloads — all defined as infrastructure as code.
• Own delivery end to end: the CI verification pipeline, release promotion, and gated rollouts with migrations, smoke verification and automatic rollback.
• Operate the production database: schema migrations, capacity planning, replication, backups and recovery.
• Write and test infrastructure, delivery and operational code in TypeScript, held to the same review and testing bar as product code.
• Own the security gates in the delivery pipeline and the least-privilege access that deploys run under.
• Operate the AI runtime: model routing and failover, credential management, cost attribution, and the eval pipelines that gate changes.
• Carry on-call with the rest of the team, and shape the SLOs and error budgets that come with scale.
• Contribute to the design and implementation of new products and features while also enhancing the existing product suite.
• Be a mentor for colleagues and help promote knowledge-sharing.

Qualifications

We don’t expect anyone to match every line below. If most of it describes you, we’d like to hear from you.

• Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI’s potential impact on the function or industry.
• Current, hands-on fluency with AI-assisted and agentic development. We expect you to work this way.
• Experience leveraging AI/ML in engineering and quality processes (e.g., automated testing, AI-driven insights, intelligent monitoring).
• 12+ years of experience in DevOps, platform or infrastructure engineering, with a track record of delivering high-quality products.
• Deep AWS experience, operating production platforms at scale.
• Strong proficiency in TypeScript.
• Infrastructure as code in a general-purpose language — AWS CDK, Pulumi or similar.
• Experience running containerized services in production.
• Experience with software development lifecycle (SDLC) and automation — implementing automation, testing strategies, and CI/CD practices across delivery stages using GitHub for version control and GitHub Actions for automated build, test, and deployment workflows.
• Experience with PostgreSQL database management.
• Experience with AI/ML microservice integration.
• Experience operating inside an enterprise cloud-governance regime — service control policies, mandated naming and tagging, restricted IAM, region allowlists — and delivering within them.