Job Opportunities API

At Appfire, we believe that great work happens when people get to choose how they work. After 20 years of creating software that empowers teams to break silos and collaborate seamlessly, we've learned that one size does not fit all. We’re a team of 800+ employees, working remotely across 28 countries. Our flagship products include: Appfire Flow, JXL, Comala Document Management, 7Pace Time Tracker, Jira Misc Workflow Extensions, and BigPicture. Here you can read some of our customer stories: https://appfire.com/resources/resource-library/customer-stories About the role Building an AI agent is easy. Teaching it how a specific enterprise actually works is hard, and most organizations build that knowledge from scratch. Appfire has spent years encoding it into our products already. This role turns that expertise into packaged, plug-and-play AI skills that work across the AI agent platforms our customers use, plus a way for enterprises to see and govern which skills their agents are running. You'll own two things that need each other to work well. Packaged skill content without a way to manage it becomes hard to trust at scale. A management layer without real content behind it takes too long for customers to see value. What you’ll own Packaged AI skills. Turn expertise from across our product line into skills an AI agent can call on, so agents behave more like an experienced admin or program manager instead of starting from nothing. You'll define the packaging format, the delivery model, and the go-to-market plan with each product team. This ships as a standalone product ahead of the management layer. A skills management layer. Once we've validated demand for packaged skills, build the lightweight layer that lets enterprises track what they've bought: version history, ownership, and visibility into which agents use which skills, something most enterprises can't answer today. Build only what customers actually ask for. Delivery architecture and its tradeoffs. We're planning to deliver these skills through Appfire-hosted endpoints rather than files customers download and run themselves. That approach raises open questions we haven't answered: what data residency and compliance posture we'd need to support, and how a cost structure tied to usage rather than seat count should shape pricing. You'll help figure out whether this is the right model and what it would take to commit to it. Business model. We have a working hypothesis for how this gets priced and packaged. It's not tested. You'll help validate whether that structure holds, or find a better one, and pressure-test pricing and packaging as real customers start buying. Policy requirements, as a consumer. A separate team owns the policy engine that decides what any agent, including one running your skills, is allowed to do. You won't own that system, but you'll bring it clear requirements, like what a Jira admin needs to be able to restrict about how a skill behaves, so it gets built once, correctly, instead of two teams solving it in parallel. What success looks like A growing catalog of packaged skills, sold and adopted by existing enterprise customers by the end of 2026 Clear signal on whether packaged skill demand justifies building the management layer, and with what scope Data residency and delivery commitments documented and signed off before the management layer ships Adoption of the management layer among enterprise customers by Q2 2027 A working requirements pipeline into the policy engine owned by our governance team, with no duplicate work What you’ll need Several years of experience as a product manager who has taken a product from 0 to 1 and owns the business case, not just the roadmap Experience with usage-based or hosted SaaS pricing, where infrastructure cost doesn't map cleanly to seat count Comfort defining a new delivery architecture and the compliance tradeoffs that come with it A track record of