Forget building AI from a Silicon Valley office. One of tech’s fastest growing jobs is sending workers directly to customers to configure AI tools, integrate software, and solve complex business problems.

Job postings for “forward-deployed” engineers rose more than 1000% between January and August 2026, compared to the same period last year—and more than 4,600% compared to 2023, according to Lightcast data. That far outpaces the broader tech job market, where postings grew 13% year over year.

Similar growth has been reported on LinkedIn and Indeed, according to The New York Times.

The concept isn’t entirely new. Palantir has long been known for its forward-deployed model, in which technical employees work closely with customers to build and implement software in the field.

Now, as companies race to effectively deploy AI into business processes, that model is spreading like wildfire.

“Companies are increasingly tapping into powerful AI models and struggling to turn those models into something that actually works inside of their business, as connecting them to proprietary data, existent systems and specific workflows can be a big roadblock to overcome, Paul Farnsworth, president of tech career platform Dice, told Fortune. “Forward-deployed engineers can help fill that gap.”

And the jobs come with a substantial paycheck. Lightcast data shared by Farnsworth found that the median advertised salaries for forward-deployed engineers was more than $188,000—compared to roughly $145,000 for traditional software engineers.

At some tech giants like Anthropic, compensation for some forward-deployed roles can even reach $400,000.

The Palantir brainchild that’s spreading across tech firms

Palantir currently has around four dozen open forward-deployed positions, mostly in software development. Candidates have the opportunity to apply for client-specific opportunities, including major corporations like Intel, defense organizations like NATO, and governments like Norway.

“As an FDSE, your responsibilities look similar to those of a startup CTO: you’ll work in small teams with minimal supervision and own end-to-end execution of high stakes projects,” a Palantir job listing said. “Your day might span discussing architecture with fellow engineers, wrangling massive-scale data, coding a custom web app, speaking with customer executives, or establishing strategy for your team.”

That hands-on approach has become a defining part of Palantir’s business model—and one the company credits with helping it compete against much larger technology companies.

“We hired the best software engineers in the world, ejected them from the comfort of a Palo Alto office, and dropped them in remote locations to spend their days in the service of incredibly skilled but non-technical operators,” Meline von Brentano, Palantir’s head of digital transformation strategy, wrote in a blog post last month. “In the process, we beat out much better resourced companies in the race for the best talent.”

And by many metrics, it’s been successful. Palantir’s market cap now sits at over $400 billion, and in the company’s most recent quarterly earnings, the tech firm reported revenue increases of 93% year-over-year, totaling $1.94 billion.

Many of its competitors have begun adopting the same playbook.

Microsoft, Meta, Google, OpenAI and Anthropic currently all have openings for forward-deployed engineering roles. Others, ranging from established giants like Nvidia to startup unicorns like Scale AI, have also adopted the “forward-deployed” model for other job categories, too, including in product management and tech architecture.

How to land a forward-deployed engineering job

Becoming a forward-deployed engineer isn’t easy. The role requires a mix of technical expertise—including programming, machine learning, generative AI, and tech infrastructure—paired with the consulting, communication, and leadership skills needed to work directly with customers.

For those interested in landing a forward-deployed engineering role, Farnsworth said it’s critical to start with modern tech fundamentals and then build expertise in APIs, data pipelines, cloud infrastructure, and how to get AI systems reliably into production. From there, workers should lean into the softer skills like problem-solving, communication, and business judgment.

“Just knowing how to use the latest model or AI tool isn’t enough anymore. The bigger differentiator is being able to connect that technical knowledge to a business problem,” Farnsworth said. “Can you walk into an ambiguous situation, understand how a workflow actually operates, communicate with technical and nontechnical stakeholders and build something that creates a measurable result?”

Workers already in tech can build that expertise in their current roles by finding opportunities to put AI into real business processes.

“I’d also encourage tech professionals to look for opportunities in their current roles to deploy AI into real workflows and document the impact—whether that’s revenue generated, time saved, errors reduced or a process improved,” Farnsworth added. “Focusing there will help those looking for forward-deployed roles be competitive and land the job.”