Engineering Manager, Postman AI

The Opportunity 

Agent Mode and AI Engineer are two of our most exciting AI products. Agent Mode is the foreground product where developers interact with an AI that understands their entire API workspace. AI Engineer handles long-running development and analysis tasks autonomously across an organization’s API surface area. You’d be working with the team building and integrating these into Postman’s product surface area

What we actually need from you

You manage by doing. You’re not running standups and writing status updates while engineers do the actual work. You’re in the code, reviewing PRs, making architectural calls, and shipping alongside your team. You have opinions about what good engineering looks like when a significant chunk of code is AI-generated, and you hold the team to that bar through reviews and design discussions, catching problems early.

You use AI to run a better team. Not just as a product you’re building, but as a tool you’re using. Tracking work, surfacing risks, managing dependencies. The expectation is that you find ways to get more out of a small team than the headcount suggests, and AI tooling is a big part of how you do that. This is a necessary constraint for us to build a best-in-class AI-native product.

You grow engineers by putting real problems in front of them. You know when someone is ready to take on more scope and when they need support first, and you act on that read rather than waiting for a performance cycle to surface it.

You care about how the system fits together. Agent Mode and AI Engineer sit on top of the Context Graph, Fabric Gateway, filesystem-native collections, and a growing tool surface. You need to understand where the seams are and what breaks when something changes upstream.

What the work looks like

Own the engineering roadmap across Agent Mode and AI Engineer: alignment with product, unblocking engineers daily, sprint cadence, and quality as output velocity goes up

Drive architectural decisions and code quality across backend systems, with enough hands-on involvement to know when something is going sideways before it ships

Partner with product, design, and GTM to figure out what AI-native API development actually looks like for enterprise teams.

Work directly with customers and field teams to understand where the product falls short and feed that back into engineering priorities.

Mentor engineers and expand their scope to build a team that can operate at higher levels of autonomy over time.

The basics

7+ years of backend engineering experience with solid architectural depth. You’ve designed systems at scale and can read a design without getting lost in the implementation

At least a year of managing a team with direct IC reports, and a track record of engineers getting better when working with you.

Hands-on, as a default. You code regularly to ensure you’re best positioned to build an AI-native product, and to stay comfortable in a space where the tooling changes every few months.

Nice to have

Exposure to agentic architectures, LLM tool use, and MCP. Experience with observability platforms or developer tooling.

Why this matters

The foundation has shipped. Git, filesystem, Fabric Gateway, and Context Graph are all in production. The work is shifting toward quality, coverage, and enterprise depth across both products. If you’ve been managing engineering teams and you’ve been thinking about what software development looks like when agents are doing a meaningful share of the work (and you want to build that, not just talk about it), this is the role.