The modern military faces a challenge in translating the enormous capabilities of AI into reliable operational outcomes. This gap between technological capability and operational value of AI in defence operations depends on the specific data, context, systems, workflows, and operational conditions under which it is deployed. Forward-Deployed Engineering offers an institutional mechanism to close this gap by embedding engineers close to users and feeding lessons from deployment back into product development.

Introduction: Conceptualising Forward-Deployed Engineering

Modern military capability is increasingly defined by and dependent on software, Artificial Intelligence (AI), cloud infrastructure, data and digital networks. Despite this, the outcome of a mission remains of paramount importance to the military, not just the acquisition of the latest technology.[1] These missions are often complicated and dynamic, dependent on data and operational context.[2] Workflows change quite regularly depending on the battlefield reality, while the data remains classified. Additionally, different military administrations may have very different needs.

Two military units might both want AI for intelligence, but one may need help analysing drone footage. In contrast, the other may need to combine satellite imagery with other intelligence sources. There isn’t necessarily one standard product that works for all of them. Even within a single military unit, mission objectives differ. Counter-proliferation, counter-terrorism, and logistics all have different requirements. A one-size-for-all approach or product rarely fits.

When Palantir Technologies, an American software company established in 2003, first encountered this problem with its clients in the American defence establishment, its solution was simple: embed its engineers on-site.[3] They created a model in which software engineers were embedded with operational users or deployed alongside them, allowing them to observe problems first-hand, modify software rapidly, and continuously incorporate user feedback into the product development cycle. This is what led to the emergence of Forward Deployed Engineering, or FDE in short.

The term originates in the military, where a ‘forward-deployed’ soldier is posted on the field, close to the action and ready to respond.[4] In the world of technology, the FDE (Forward Deployed Software Engineer) is deployed on-site with a client/user to help them adopt complex software and solve real problems, feeding what they learn back into the core product.[5] At Palantir, the FDEs were initially named ‘Deltas’, with their mission being ‘to deploy and customise Palantir platforms to tackle critical business problems, and measure success by the customer’s outcomes’.[6]

For a defence/military force trying to integrate AI within its infrastructure, an FDE can assume a hybrid role, combining several roles—that of an engineer who understands the technology and can modify or build software, a product strategist who understands what the military actually needs and figures out how the technology should be adapted to meet that need, and finally that of a field operator who spends time with the actual military users of the technology and understands how things work in real operational conditions.

Figure 1. Role of a Forward-Deployed Engineer Source: “What is a Forward Deployed Engineer? Role, Skills, and Why It Matters”, Datacamp, 17 July 2026.

Defining Forward Deployed Engineering

Even though the practice and the term were both put forth by Palantir way back in 2006, Forward Deployed Engineering lacks a proper academic definition. The current definitions or explanations can be found in job postings at OpenAI or SarvamAI, as well as in some blog posts.[7] A paper published earlier in 2026 claims to define the term for the first time in an academic fashion. It sheds light on the concept through three properties and, in the process, also helps distinguish the practice from other forms of engineering or traditional consulting. It defines a Forward Deployed Engineer as a software engineer embedded at a client organisation by its parent product organisation ‘to deploy, customise, and co-evolve the company’s technology, while maintaining a direct feedback loop to the product organisation’.[8]

Forward Deployed Engineering is defined as an organisational practice that deploys such engineers, characterised by three fundamental properties:

Product ownership: The embedded/forward deployed engineer remains an employee of the parent company with direct influence on a proposed design plan of the product.[9] By virtue of working for the parent technology company, they can also bring their on-field observations back to the company’s product development team. This serves many purposes—an FDE can build on the existing product platform rather than reinventing the wheel. So, if a military organisation wants a solution to a specific combat issue, the FDE can take existing technological and product capabilities and adapt and combine them to address that problem. This helps the FDE to focus on domain-specific defence integration of the platform, tailoring it to a specific military context, rather than building a new platform or product from scratch. The FDE’s incentive, thus, lies in solving the problem rather than perversely prolonging the engagement.[10] This is crucial from both military technology and economic perspectives, since it reduces costs while accelerating adoption of military technology.

This helps the FDE to focus on domain-specific defence integration of the platform, tailoring it to a specific military context, rather than building a new platform or product from scratch. The FDE’s incentive, thus, lies in solving the problem rather than perversely prolonging the engagement.[10] This is crucial from both military technology and economic perspectives, since it reduces costs while accelerating adoption of military technology.

Bi-directional knowledge flow: An FDE does not simply bring a company’s technology tool or platform to the military, nor does it just bring military requirements back to the company. The FDE model creates a continuous two-way exchange of knowledge between the technology developer and the military user.[11] Essentially, the FDE acts as a bridge between the two sides. It briefs a military unit on the capabilities of its technology/AI platform and how to use it in different situations, helping the military understand the technology and exploit it more effectively. But the flow doesn’t stop there. The military informs the FDE about the issues they actually encounter and what they need the technology to do in specific scenarios. They share information about system failures, unforeseen situations that developers may not have anticipated, etc. Subsequently, the FDE takes these observations back to the parent company. This bi-directional knowledge flow creates a loop that converts initial deployment........

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