New AI Job Titles · Delivery
Forward Deployed Engineer (FDE)
A Forward Deployed Engineer embeds directly with a customer after the contract is signed and builds the AI application inside that customer’s environment. The title originated at Palantir and is now posted by Anthropic, OpenAI, Meta and ByteDance. It is the post-sale counterpart to the Applied AI Architect, who designs the deployment before it is bought.
Where did the Forward Deployed Engineer come from?
Palantir. The company built its entire delivery model around engineers placed inside the customer organisation, working on the customer’s problem on top of Palantir’s platforms rather than shipping a product and handing over documentation. That is a decade-plus of precedent, and it is the single most useful fact for understanding why the AI labs picked this title instead of inventing one. They were not naming a new job. They were importing a delivery model that already had a track record in a business with the same shape: expensive platform, high-context customer problem, and no clean handoff.
Our Palantir salary guide covers the original FDE track in detail, including how the role sits in that company’s career structure.
Which companies are hiring FDEs?
- Anthropic posts Forward Deployed Engineer, Applied AI in New York, San Francisco, Seattle, Munich and Paris, plus a Federal Civilian variant. The job is embedding with strategic customers and shipping AI applications against real business problems after the sale.
- OpenAI has more than twenty open requisitions across San Francisco, Tokyo, New York, Paris, Seoul, Singapore, Sydney and Abu Dhabi, with Life Sciences, Semiconductor and Government variants. Scope is discovery through production for frontier-model deployments at strategic enterprise and government customers.
- Meta hires Forward Deployed Engineer, Enterprise AI, embedding with enterprise partners to integrate Meta’s foundation models and Llama into the partner’s products.
- ByteDance / BytePlus has posted the role in Singapore with a job description that is explicitly about building AI agents: prompt optimisation, knowledge and memory-base management, tool use, and observability.
The ByteDance posting is the one to read closely if you want to know where this is going. It applies the embedded-delivery model directly to agent deployment, which is the part of AI adoption that currently fails most often between demo and production.
How is an FDE different from an Applied AI Architect?
One line separates them: who writes code in the customer’s environment. The Applied AI Architect works before the deal, advises across the customer’s stakeholders, and hands over an evaluation and a deployment design. The FDE works after it, sits inside the customer’s team on the customer’s stack, and produces running software. Everything else about the two roles follows from that.
At Anthropic both roles sit inside the same Applied AI organisation, so the handoff happens internally. Note also that some Anthropic postings render the functionally identical role as Applied AI Engineer. That label travels less reliably than the work does: xAI uses Applied AI Engineer for applied product and recommendation engineering with no customer embedding at all. Read the responsibilities, not the title.
What does this mean if you are buying AI?
It means the vendor has accepted that their model does not deploy itself, and has budgeted an engineer to sit in your building until it does. That is a stronger commitment signal than any implementation SLA, and it is worth asking for explicitly during procurement. It also changes who you need on your side: an embedded vendor engineer is only as useful as the internal owner they work with, which is normally an AI Engineer or the Chief AI Officer’s delivery team.
Role scope verified against live postings: Anthropic, Forward Deployed Engineer, Applied AI · OpenAI, Forward Deployed Engineer (FDE) · Meta, Forward Deployed Engineer, Enterprise AI (August 2026).
Forward Deployed Engineer: common questions
Where did the Forward Deployed Engineer title come from?
Palantir. The company built its delivery model around engineers who work on the customer’s site, embedded in the customer’s team, building on top of Palantir’s platforms against a specific problem. The title carried that meaning for more than a decade before the AI labs adopted it, which is why it arrives with an established job description rather than a new one.
Which companies are hiring Forward Deployed Engineers now?
Anthropic posts Forward Deployed Engineer, Applied AI across New York, San Francisco, Seattle, Munich and Paris, plus a Federal Civilian variant. OpenAI has more than twenty open requisitions spanning San Francisco, Tokyo, New York, Paris, Seoul, Singapore, Sydney and Abu Dhabi, including Life Sciences, Semiconductor and Government verticals. Meta hires Forward Deployed Engineer, Enterprise AI. ByteDance’s BytePlus has posted the role in Singapore.
Is Applied AI Engineer the same role?
Sometimes. Some Anthropic postings render the functionally identical role as Applied AI Engineer, so at that company the two labels can mean the same job. Elsewhere the label is looser: xAI posts Applied AI Engineer for applied product and recommendation work that is not customer-embedded at all. Read the responsibilities rather than the title, and check specifically whether the job describes working inside the customer’s environment.
How is this different from an Applied AI Architect?
The Architect works pre-sale and designs the deployment. The Forward Deployed Engineer works post-sale, sits inside the customer team, and writes the code. At Anthropic both roles report into the same Applied AI organisation, so they are two halves of one delivery motion rather than competing titles.
What does a Forward Deployed Engineer earn?
Compensation for the title at the AI labs is not yet publicly benchmarked, since most of those requisitions are recent. The longest-running data point is Palantir, where the FDE track is well established and covered in our Palantir salary guide. Numbers from that track are not a reliable proxy for a frontier lab, where equity structures differ substantially.
