Founding Forward Deployed Engineer

Founding Forward Deployed Engineer You’re a builder who works at the frontier with our customers. You deploy Nessie into customer environments, build the integrations and workflows they need, and bring what you learn back into the core product. We’re two people with more real customer pull than two people can carry, so you’re the technical and product force that makes deployments real, and you wear the hats a tiny company needs. You make our customer operations and relationships faster across the board. --- What "build" means here You have shipped something real: something with users, or something you use every day because you made it for yourself. You have gone from nothing to working software more than once. You’re comfortable across the stack. Our codebase is Swift/SwiftUI (macOS app), Go (backend), and TypeScript (services). You do not need experience in all of these. You need to be the kind of person who picks up what they need. You reach for AI tools instinctively (Claude Code, Cursor, Codex) and you are faster because of it. If your first instinct under pressure is to stare at the code instead of handing it to an agent, this is not the right fit. --- What you will work on Core engineering Cross-platform conversation sync across many AI providers, the hardest unsolved capture problem in the space Search and retrieval that makes thousands of conversations queryable in milliseconds Ontology and knowledge structuring: turning messy conversational material into trustworthy, typed knowledge AI governance: team sharing, permissions, and policy. This is what turns Nessie from an individual tool into the context layer for a whole organization. Agent-facing APIs (CLI, MCP) that let any AI tool reach accumulated human reasoning Self-hosted and on-prem deployments, plus the security and compliance that come with them, as we move into larger and more regulated organizations The intelligence layer that sits underneath every AI interaction Agent-trace intelligence: extracting the first-class signal that lives only inside AI sessions and agent traces into a queryable layer for observability, eval, and self-improving agent workflows Forward deployment Embed with a customer to deploy Nessie into their environment: onboarding, the team-sharing and permissions rollout, integrations, and live troubleshooting, alongside the founders. You shadow first; the founders stay the relationship leads. Increasingly this includes self-hosted or on-prem setups for larger or regulated orgs. Own the customer feedback loop operationally: triage, reproduce, drive the fix with us, and make sure nothing slips. Build the integrations and glue a specific customer needs, in a way that re-packages into the product. Absorb operational work so we can all keep shipping. What you work on in week 1 may differ from week 4. A bit of everything We keep this part intentionally broad. On a two-person team, beyond shipping product you'll help with internal ops, owning customer relationships, and the work that does not fit a job title. If you want to only write code and never touch anything else, this is not the role. --- What you will NOT need A specific degree or school Prior startup experience A perfect resume Permission to try things What you will need The instinct to ship before it is perfect Extreme autonomy. We are two people. There is no manager. There is no spec. There is a problem and you figure out how to solve it. Opinions about products you use. If you have never looked at an app and thought "this is wrong and here is how I would fix it," we are probably not a match. Comfort with ambiguity. The product is evolving fast, and what you work on in week 1 may differ from week 4. That should excite you. --- Logistics San Francisco, in person. $100K-150K salary, 0.5%-1.0% equity. We’re open to sponsoring work authorization (including H-1B) for the right person. How to apply Show us something you built. A link to a project, a repo, a product, a tool. If you do not have something to show, build something this week and send it. We care about what you make, not what you say you can make.