Senior Forward Deployed Engineer

1 нед. назад

USASeniorOnsite

ai systemssystem architectureproduction deployment

Build and deploy cutting-edge AI systems directly with clients to solve real-world problems at the edge of AI capabilities.

Обязанности

You own the outcome. You work with the customer, frame the problem, choose the architecture, build the system, ship it, and stay accountable for what happens in production:
Discover. You embed inside a real business, learn how it makes money, and find where AI would create real value rather than a demo.
Decide. You turn ambiguity into a product direction and a technical plan, and you defend both when someone senior disagrees.
Build. You ship the system, not a disconnected piece of it, and you make the build-versus-buy and architecture calls yourself.
Own. You measure what happens in production and keep improving it after the merge.
At this level you own a workstream outright. You decide what gets built and in what order, you are the technical voice the client hears on that work, and when the scope turns out to be wrong you are the one who says so and re-cuts it. You are closer to a founder inside an engagement than a contributor on an assembly line.

Другое

Our mission is to turn frontier intelligence into real results for every business. We charge for results, not access.
Tenex was founded in New York City in 2025. We are roughly 50 people today and our end-of-year target is 150. We ship production AI for Fortune 500 clients, and one in three of our engineers has founded a company. Our engineers work directly with C-suite leaders to find where AI can change their business, and then build the custom systems that make it work in production at the boundary of what is possible.
The Senior Forward Deployed Engineer is how that happens. It is not a support role and not a services role. It is the role.
We now have superintelligence on demand, but model capabilities are advancing faster than companies can adapt, so most of that value goes untapped. The hard part starts after the model. Building reliable systems around frontier models means connecting fragmented data, rethinking workflows from first principles, building evaluations and controls, and adapting as fast as the frontier labs ship.
The most important work now happens at the edge, where AI meets real world conditions. That is the only place we work.
Tenex is rebuilding the software development lifecycle around coding agents. The goal is a software factory that carries work from a business problem to a production system with increasing agent autonomy, where planning, architecture, implementation, testing, review, and delivery become one connected system rather than a series of handoffs.
You will learn how to structure work for agents, engineer durable context, evaluate outputs, and decide where deterministic software and human judgment remain in control. The system is early, it is already used by everyone here, and it provides real leverage today. Engineers who join now will help decide how it works.
This matters beyond your own engagement. Every engagement produces reusable agent systems, evals, and tools that make the next one faster, so the work you do compounds instead of ending when the client signs off.
Every engagement changes the problem. Each one brings a different industry, architecture, and set of technical constraints, across finance, software companies, media, industrials, energy, logistics, professional sports teams, healthcare, consumer packaged goods, real estate, and market research. That exposure keeps the work interesting and forces you to learn faster than you have anywhere else.
Recent work includes the operating system a private equity firm with $115 billion under management runs on, AI verification of every in-store sampling station for a national retailer with 70,000 field staff, and camera systems across thousands of retail stores that catch theft, manage queues, and track inventory on the floor.
Some of what we hit has no established solution yet, including agent orchestration, evaluation, memory, and long-running execution. You will work at the boundary between what the newest models appear capable of and what can actually be made reliable in production.
Tenex has more demand than capacity. New engagements, products, and teams create a constant need for people who can own larger problems, so nobody here waits for a seat above them to open. Engineers who deliver are trusted with broader technical decisions, more important client relationships, and greater responsibility across the company.
One year here is worth several years elsewhere in engineering, product, customer, and leadership growth, because the mechanism is the work itself rather than a development program.
We are a people business. The engineers we put in front of clients are the product, so hiring is the highest-stakes decision we make each week. The pattern we bet on is the high-slope generalist, meaning a strong engineer who has shipped real production software, moved hard into AI, and improves faster than their peers. Years of experience matter less than slope.
Specifically, we look for engineers who meet this bar:
You have shipped production software that real users depended on and that you stayed accountable for after launch.
You have built something real with LLMs, and you can explain what made it reliable rather than just impressive.
You can walk into an unfamiliar domain and be genuinely useful within days.
You can explain your decisions to a CEO as clearly as you can to another engineer.
You already work with coding agents and have real opinions about where they help and where they do not.
Tenex is intense by design. We work together in Manhattan five days a week, the pace is fast, and the standards are high. We genuinely like one another and love working here. People share discoveries, challenge each other's thinking, and step in to help, so the bar is high and so is the support around you.
This is probably not the right environment if you want a narrow scope, a predictable pace, or distance from customers. It is built for engineers who want responsibility, difficult problems, and a steep learning curve. We turn away client work rather than lower the bar, and that is the point.
Compensation has three parts. Base salary is a strong guaranteed foundation, and it is deliberately the floor rather than the headline. The quarterly bonus rewards meaningful delivery, quality and outcomes, and leadership, and it is not capped at target, so high performers earn well above their base. Equity makes you an owner in the value you help create, and everyone at Tenex owns a stake in every bet we make, including the products and joint ventures that come out of client work. We share the full mechanics, and your specific numbers, with your offer.
Six steps, no hidden criteria, and fast decisions:
Recruiter conversation, 15 minutes. We cover your background, your goals, and what you want from your next role.
Behavioral interview, 30 minutes. We talk about how you work and the decisions you have made.
Technical screen. A practical HackerRank exercise you complete on your own schedule.
Systems design. A live discussion where you work through the architecture and tradeoffs for a real-world system.
Team and final round. You meet more of the team, then speak with the co-founders.
Decision. We debrief quickly and give you a clear answer.
Our interviews feel like the job rather than a quiz show. There are no trick questions and no hidden criteria. Come ready to explain how you think, discuss tradeoffs, and show how you use AI in your work. Bring your hardest questions, because those are the ones we enjoy most.