What is a forward deployed engineer (FDE) for MSPs? A forward deployed engineer (FDE) is a software engineer who embeds with a client to design, build and optimize workflows across departments and data systems, increasingly using AI. For MSPs, FDEs open a new revenue model that pairs one-time project work with ongoing subscription support. MSPs can build this capability by upskilling their team, hiring or partnering.
You may already have a managed AI service line that includes AI readiness assessment opportunities and pre-built AI agents. But you know your clients are needing complex and customized agentic AI and data solutions beyond chatbots. You're currently strategizing as to how best to realign your organization to better serve your client and seize the AI opportunity.
As you are wrestling with this challenge, this is what is going on in the larger market. “The MSP channel will be the forward deployed engineers [FDE] for small and midsize businesses,” Craig Donovan, COO, Pax8, recently said. This is the landscape. The answer to this problem is forward deployed engineers.
What Is a Forward Deployed Engineer (FDE)?
An FDE, a term first used in the military and then later reimagined by Palantir, is a software engineer role that embeds themselves in their client’s organization to design, build and optimize their workflows across departments and data systems, now leveraging AI & data.
An FDE requires a set of specialized skills that, at a minimum, include a strong engineering background and industry-specific specialties. On top of that, they can effectively collaborate with their team, are comfortable working in rapidly changing environments, constantly iterating on client projects and most importantly, eager to continuously learn and make decisions with minimal supervision.
If you have people in your organization that match this description, you already have FDEs. If you don’t, you may be missing a significant revenue opportunity.
Unlocking High-Margin AI & Data Revenue: The Math Behind the Opportunity
Total Revenue
The subscription is a critical component—it provides the client a predictable cost for maintaining the workflow. It gives the MSP an opportunity to demonstrate their value in monitoring and supporting the workflow. Now, imagine scaling across all your clients, multiplied with the workflows per client. If the revenue math gets you excited about the opportunity, you need to focus on learning how AI & data work, which leads to decisions about whether to hire or partner.
Master Your AI & Data Stack: Deep-Dive Learning & Tooling Strategy
You are going to have to make some decisions about what part of AI you are going to address. It depends on many factors that include what industries you’ll need to specialize in, what stages of development you’ll be deploying AI and data for your clients, and which workflows you’ll be optimizing. To make these decisions, you’ll need to start with learning.
First, to help you and your team understand how AI, and specifically how LLMs work under the hood, seek qualified resources from industry experts, like OpenAI’s co-founder Andrej Karpathy’s YouTube channel. AI is much more than just vibe coding and desktop agents. It has multiple parts that include agentic workflow orchestration and automation, data processing and analysis, loop engineering, and enriching your business decision-making capabilities.
Second, try to standardize your toolsets which includes selecting a solid data analytics platform and which AI models to use. As tempting as it is to skip the data step and go straight to AI models, don't do it! Data is the fuel of AI. If your data sources are not clean, your AI’s output will be garbage. With clean data sources, you will enable your team to build customized-specific agentic workflows that deliver high-quality results to streamline your client’s operations and elevate their productivity to higher level thinking.
Build Your In-House FDE Team: Skill Gaps & Salary Investment
You are already sending technicians into your client’s environment and interacting with them—an FDE does the same. What differs between the roles relates to technical depth and daily responsibilities.
Your technicians deal with day-to-day operational tasks that include routine IT support, maintenance and system monitoring. FDEs are looking more broadly at business problems and processes and then build custom software integrations, data pipelines and advanced reporting.
You, as an MSP, need to take a hard look and assess the current skills gap you have. Then, you must decide whether you have enough client work to keep the FDE busy. The FDE is an expensive role that has an estimated salary range of $135,000-$200,000 USD (Palantir job posting reference here). This is not a "one size fits all" role—some FDEs may have industry or functional expertise such as healthcare or finance. This means you'll likely need more than one FDE. If hiring is not a viable option due to cost, then think about partnering.
Strategic Partnerships: Scale AI & Data Expertise Without the Overhead
Partnering helps you bridge the skills gap of AI and data without the heavy overhead costs of a fulltime hire. It helps you and your team move fast on your clients’ projects. As previously stated, there are different types of FDEs, so partnering allows you to align the expertise to your client needs.
A good partner will also be secure enough in their own role that they share their knowledge freely and help upskill your team and your client's team.
Are You Ready? Key Questions for Your MSP Leadership
Ask yourselves these questions to decide whether to hire or partner with FDEs:
- Do you have enough complex, client-specific AI and data work right now to keep a dedicated FDE fully utilized?
- Does your current team have the specialized software engineering and data skills required to build custom agentic workflows, or is there a critical gap?
- Can your budget absorb the high fixed salary of a full-time FDE ($135,000–$250,000 USD), or does a flexible partnership make better financial sense?
Whether you build the capability in-house or partner to move fast, the opportunity in agentic AI won’t wait. Take the step that positions your MSP as the essential forward deployed team for your clients today and start accessing a new, ongoing revenue stream.
Use the MSP calculator to understand your revenue opportunity.
About the Authors: Linh Phan and Mark Clancy are co-founders of Khashmere. As forward deployed engineers, Khashmere enhances MSPs’ AI & data capabilities to solve your customers’ toughest business problems.