Forward Deployed Engineer

Tenex Labs is hiring a Forward Deployed Engineer in New York, United States. It pays $224k-$394k a year and Level rates it ; you can apply on Tenex Labs.

Level's read on this job

On Level's scale, this forward deployed engineer role is Builds AI ●●●●: the job is building AI systems.
Pay on this posting starts 23% higher than the typical forward deployed engineer posting on Level.
The posting mentions OpenAI, Anthropic and Cursor among its tools and skills.
Level classes it as a senior role.
Tenex Labs has 21 other open roles on Level.

AI in this role

Build and ship frontier AI systems, LLM integrations, and autonomous agents directly for Fortune 500 clients.

openaianthropiccursorpythonllms

computer-visionfull-stackprompt-engineeringai-agentssystem-architectureclient-facing

Tenex builds frontier AI that works in the real world. Our engineers sit with C-suite leaders, find where AI adds the most value, and ship bleeding-edge AI to production.

We were founded in New York City in 2025. We are currently 70 people and will double by the end of the year. We build for Fortune 500 companies across media, healthcare, retail, finance, and sports.

Anthropic, OpenAI, and Cursor are partners where we turn technology into reliable systems businesses use every day.

The Role

You’ll own client projects end to end: find where AI adds real value, decide the technical plan, build the whole system, and keep improving it in production. You’ll lead a few projects at a time in a pod run by an engineering manager.

We look for engineers who:

Have shipped and supported production software.
Have built reliable systems with LLMs.
Can explain decisions to a CEO or an engineer.

You will learn to structure work for agents, engineer context, evaluate outputs, and decide where people stay in control. Every project leaves behind agent systems, evals, and tools that make the next one faster.

The engineers we put in front of clients are the product, so hiring is the most important decision we make each week. Our engineers have worked at Google, Meta, Amazon, Microsoft, AWS, DoorDash, Coinbase, and Oracle, and many have founded companies.

Our Work

Sales intelligence for a sports and entertainment company. Models score 4.1M fans every night, and an LLM explains each score for sales reps. Top-ranked fans buy at 125x the rate of fans who are not called.
Shelf and field intelligence for a beauty brand. Revenue forecasts for every shelf move, field staffing optimization, and AI checks of shelf photos. Fixing the retailer data feed alone recovered about $1M a week in sales.
In-store computer vision for a retail analytics company. Vision models run on edge devices in each store. They count 98% of entries with zero false counts, and store no video or faces.
AI legal review for true-story TV scripts at a global media company. Attorneys start from an AI first pass that flags defamation, false light, and privacy risks. A review that took about 7 hours now takes about 1.

How We Pay

Most pay models were built before AI changed how fast engineers can work. Ours wasn’t: you get a base salary plus an uncapped quarterly bonus based on the work you ship, so the more you do with AI, the more you earn. Last quarter, every full-quarter engineer beat their baseline.

OTE $224K-$394K • Offers Equity • Offers Bonus • 55/45 split

How We Work

Tenex is intense by design. The pace is fast, and the standards are high. People share what they learn, challenge each other, and step in to help, so the bar is high and so is the support.

This is probably not the right place if you want a narrow scope, a predictable pace, or distance from customers. It is built for engineers who want responsibility, hard problems, and a steep learning curve.

Our Vision

We’re bootstrapped and profitable, and we reinvest what we earn into tools, research, and products of our own. Over time, that’s how we build a modern-day Bell Labs: a place where solving today’s problems gives us the means to tackle bigger ones.

How we rate this

Forward Deployed Engineer at Tenex Labs rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Forward Deployed Engineer is an open job at Tenex Labs.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $224k-$394k a year.
The role is based in New York City.
The job was posted on June 4, 2026.
Seniority: senior.
Applications are handled by Tenex Labs. Apply on Tenex Labs

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Computer visionFull StackPrompt engineeringAI agentsSystem ArchitectureClient FacingOpenAIAnthropic

Also common in forward deployed engineer jobs at this level

Python RAG AI agents TypeScript Machine learning Generative AI

Pay

This job starts at: $224k
Typical forward deployed engineer job: $182k

This posting starts 23% above the typical forward deployed engineer job. See forward deployed engineer jobs

Questions you could be asked

Walk me through a computer vision problem you solved, from raw data to a deployed model.
Tell me about a project where full stack was part of your work. What did you do?
How do you structure and test a prompt to get consistent output from a language model?
How do you decide when an AI agent can act on its own versus asking for approval first?
Tell me about a project where system architecture was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Computer vision, Full Stack, Prompt engineering, AI agents, and System Architecture. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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