About Uplevyl
Uplevyl builds AI-powered knowledge and community infrastructure for organizations serving women. Our products include UpGenie (our domain-specific AI assistant), WeHub (our community platform), and UpSocial (a social platform for women). We work with mission-driven partners to turn complex, high-stakes information into clear, trustworthy guidance, and to build systems that create lasting impact.
We hold a simple conviction: in high-stakes domains like rights, law, and financial security, a generic AI is not enough. The answers people stake their lives and livelihoods on need a purpose-built system with verified, native data. That is what we build, and it is why the work is urgent. AI is reshaping how the world learns, works, and earns, and the women we serve cannot afford to be left off that train.
We have also made a deliberate choice about how we build: a small team of exceptional people, paid well above market, each doing work that would normally take several. We would rather be ten people who move the world than thirty who move paper. That choice sets the bar for every hire, including this one.
About The Role
Forward-Deployed Engineer is an engineer who works where the product meets the client. You are the partner's point of contact and the person who makes our AI work in their world.
At Uplevyl, our partners are mission-driven organizations deploying UpGenie into domains where accuracy carries real consequences. Someone acting on one of our answers may be making a decision about their safety, their job, or their rights. The FDE owns that last mile: you sit in the partner calls, understand what they actually need, configure and validate the system for their domain, and carry their feedback back into the product as clear engineering priorities.
This role is equal parts technical depth and client trust. You will read the system well enough to debug it, and read the room well enough to run it.
What You'll Own
The partner relationship, end to end. Be the named point of contact for a partner deployment. Run the delivery loop: UAT cycles, release notes, working sessions, and the honest conversations when something needs more time.
Deployment and configuration. Stand up UpGenie for a partner's domain: their data, their jurisdictions, their workflows. Own the gap between a working product and a working deployment.
Answer quality the partner can trust. Design and run the testing that proves the system is right: structured test frameworks, error categorization, root-cause analysis, and validation loops over the underlying sources. When quality slips, you find why and drive the fix.
Translation in both directions. Turn a partner's ask into a spec and an estimate engineering can build against. Turn a technical decision into language a partner understands and agrees with.
Delivery workflows, automated by you. Build the AI tooling that removes manual work from delivery: validation pipelines, testing harnesses, reporting. You build these yourself rather than waiting on the core team.
Who We're Looking For
We hire across levels. A track record of building, shipping, and holding client trust matters more than years, though real client-facing engineering experience helps.
High agency. You unblock yourself. When a deployment stalls or a partner escalates, you work out the next move and make it.
Technical range. You can read a production AI system end to end: query the data, trace a wrong answer to its cause, script your own tooling, and hold your own in an architecture discussion. You use AI daily to build.
Client presence. You are calm and credible in the room, including when something has gone wrong. Partners trust you because you are straight with them and you deliver.
Rigor under pressure. You test before you claim. In our domains, a wrong answer reaching a user is a serious failure, and you treat it that way.
Sharp writing. Your release notes, status updates, and client emails are clear, honest, and tight.
A builder who ships. You have things live that prove it: tools, integrations, internal systems. You follow the frontier and form your own view on what is useful versus hype.
Judgment. You know what to surface to a partner, what to resolve quietly, and when to pull in leadership.
Even Better If
You have worked as a solutions engineer, forward-deployed engineer, technical account manager, or technical consultant.
You have deployed or operated LLM or RAG systems in production.
You have worked with legal, regulated, or otherwise high-stakes data.
You have worked in mission-driven, social-impact, women-focused, or nonprofit ecosystems.
You have founder, startup operator, or early-employee experience.
Before You Apply
We want to be direct about what this is. This is a high-bar role on a small, senior team. The work is demanding, the expectations are real, and the rewards, in compensation, in ownership, and in what you will learn, match them. If you want a defined lane and a slow ramp, this is not the right fit, and that is fine. If you want to build the AI core of a system where accuracy genuinely matters, and grow into the technical backbone of a small, ambitious team, we want to hear from you. Our interview process is thorough, and we will walk you through every step of it in our first conversation.
How We Work at Uplevyl
We finish what we start, and we do it well. We follow through on what we say we'll do, and we care about the difference our work makes.
We listen before we decide. Before we act, we ask who it actually affects: a customer, a partner, a teammate, or the communities we serve. Trust here is built the plain way, by consistently showing up for people.
We move with ownership and urgency. We don't wait for perfect information or for someone else to raise their hand. If something looks like it could go wrong, we say so early. We make the call, we move fast, and we hold a high bar for quality.
We're better together than alone. We work across teams, say what we actually think, and go out of our way to help each other succeed. Leadership here is measured by the impact you create.
We stay curious and keep learning, including how to use AI well. We hold ourselves to the bar we're building toward: questioning our own assumptions and using AI to think better and move faster.