Full-Time | Remote (United States)

You're the person who solves a problem by hand first. Pulling apart configs, reading logs, sitting in a customer's environment until you understand how things actually work. And then you figure out how to technologize it so nobody has to solve that problem by hand again. You've been called a unicorn, but your favorite animal is actually the honey badger: relentless, resourceful, and completely unbothered by ambiguity. You take as much pride in a well-written playbook or a clean slide deck as you do in elegant code, because you've learned that the right artifact at the right moment can be more powerful than any feature.

This role exists to close that gap: get inside a customer's world, understand what's really happening, and make sure our platform knows it too. You'll report directly to the CTO and work within Engineering, but your day will look nothing like a typical engineer's.

This is our first Forward Deployed Engineer hire. If every company in Silicon Valley is hiring FDEs, here's what makes ours different: you're not here to do professional services with a fancy title. You're here to make customers wildly successful while building the muscle and tooling that makes the next customer successful faster. You'll be equal parts engineer, consultant, and investigator. You don't just configure what customers ask for. You come to them with a point of view about how their IT operations should change to get more from automation, informed by their data and your experience across other environments. If you get a rush from telling a customer something true about their own processes that they hadn't seen yet, keep reading.
What we can do for you

• Make you the first person in a role that will define how Fixify works with its most important customers, with a direct line to the CTO and a mandate to shape how we do it.
• Put you at the intersection of AI, customer operations, and product, where your work directly influences what gets built and how customers experience Fixify.
• Give you the autonomy to move between knowledge configuration, tooling development, customer education, and process design based on where the highest leverage is on any given day.
• Surround you with engineers, data scientists, and operators who are building something genuinely new: an AI-native service that blends automation with human empathy in ways most companies only talk about.
• Let you see the impact of your work immediately. When you improve a playbook, tune an automation, or restructure how we capture knowledge, you'll see it in resolution times, customer confidence, and the volume of problems that never need a human again.

What you can do for us

• Own the last mile of customer success: ensuring each customer's knowledge, configurations, and processes are set up so that automation works at the right time, on the right things, with the right context.
• Dig into customer environments to extract the tacit, tribal knowledge that lives in people's heads (the stuff that's not in any runbook) and structure it into playbooks and knowledge configurations our AI can act on.
• Evaluate and tune automation performance: figure out what's firing correctly, what's missing, what's producing poor outcomes. When something isn't working, you own it. You don't escalate to engineering and wait. You treat it as an opportunity to improve the system yourself.
• Come to customers with a point of view about their own operations, informed by their data and your experience across other environments. Help them see where their IT processes need to change to get more from automation, not just replicate existing workflows inside our platform.
• Recognize patterns across customers. What you learn in one environment should make the next one faster. Turn repeatable insights into repeatable approaches.
• Close the feedback loop between the field and the product. When you see confusion, friction, or a gap, you don't just work around it. You surface it, document it, and push for it to be fixed at the source.
• Partner with Engineering, Product, Data Science, and Customer Success to translate what you're learning in the field into prioritized improvements that make every future deployment faster.

What you should bring with you

• Experience solving complex, ambiguous problems in customer-facing technical roles. Solutions engineering, technical consulting, implementation engineering, or similar work where you had to learn fast and deliver under pressure.
• Comfort writing code (Python, TypeScript, or similar) and working with APIs. You can build a script, automate a workflow, or push a fix when the situation calls for it. But your first instinct is to reach for knowledge and education before reaching for a code change.
• Working knowledge of IT operations. You understand ticketing systems, identity providers, endpoint management, and the kind of enterprise infrastructure that IT teams live in every day.
• Familiarity with AI/ML concepts and a genuine curiosity about how large language models, automation, and knowledge systems can transform service delivery.
• The investigative instinct to pull apart a customer's Okta configs, dig through their logs, trace their ticket history, and piece together why automation isn't doing what it should. Not just what the dashboard says, but what's actually happening underneath.
• A practice of producing artifacts that other people can actually use. Documentation, playbooks, operational recommendations. You know that scaling knowledge is as important as having it.
• Clear communication skills that work across audiences. You can explain a technical architecture to an engineer and explain why a process change matters to a VP of IT, in the same afternoon.
• A genuine belief that every support question is a signal, every moment of customer confusion is a product failure, and every workaround is a feature waiting to be built.
• Comfort operating in a fast-moving startup where your role will evolve as we learn. You're energized by ambiguity, not paralyzed by it.