Come build with us.
We're a small team building the runtime layer for AI agents. If that's the kind of problem that gets you up in the morning, we want to know who you are.
We're not actively hiring right now.
Faramesh is a two-person team for the moment, and we're heads-down building. When we do start hiring, this page will list real roles with honest expectations. Until then, if you're working on agent infrastructure or runtime systems and think there might be something here, we'd still like to hear from you.
What working here actually looks like.
Small team, real ownership.
Everyone owns end-to-end product surfaces, not abstract roles. You ship things that matter and you stay close to the customers using them. This is the part of company life that gets traded away as headcount grows, so we're protecting it while we can.
Open source by default.
The core is MPL-2.0 and lives in the open. The work happens in public, the design decisions get debated in public, and the code you write is code anyone can read. If working that way feels exposing rather than energizing, this probably isn't the right team.
Technical depth over generalist polish.
Faramesh sits in the runtime layer between AI agents and the systems they touch. The work is more like distributed systems, security, and policy languages than typical SaaS. We hire for people who want to go deep in one of those areas rather than people optimizing for breadth.
Honesty over performance.
We say what we think, point at the things that aren't working, and don't dress up bad ideas to spare feelings. The flip side is that nobody here makes decisions to look good in front of someone else, because nobody is performing for anyone.
The kind of work, when we do hire.
No open roles right now, but here's the shape of what's coming. If any of these sound like the work you want to be doing, reach out anyway.
Build the runtime layer.
Distributed systems, runtime enforcement, and policy language design. Strong systems thinking matters more than years of experience.
- Extend FPL with new policy primitives
- Build framework integrations (LangGraph, CrewAI, MCP)
- Harden the enforcement engine for production load
Own the developer experience.
Writing technical content, building example integrations, and running workshops. Someone who can code and write equally well.
- Write tutorials for new agent frameworks
- Build reference implementations and demos
- Run live workshops with the open source community
Find the design partners.
Talking to teams shipping AI agents, finding early customers, and shaping product direction based on real production needs.
- Source and qualify design partner conversations
- Run technical product demos with engineering buyers
- Translate customer feedback into product roadmap
Drop us a line.
No application form, no job board. Just an email. Tell us what you work on, what you're interested in, and why you're reaching out. We read everything.