There's a job title showing up everywhere in AI. Forward deployed engineer. Amazon's investing billions in expanding AI and says it's hiring thousands of them along the way. Open AI has them, Anthropic has them, Databricks, Palantir, Snowflake, and others all have versions of the role. But what is it? And more importantly, why does it matter to how vendors and channel partners are delivering AI to customers? Well, let's get into that. The idea actually isn't all that new.
Palantir has used forward deployed engineers for years. Instead of throwing software over the fence and letting customers figure it out independently, Palantir embedded engineers directly with customers. So, those engineers learned how the business operated, understood customer ideas, data, they built the integrations, they customized the workflows, and sometimes they even developed entirely new applications for a specific customer. That model became one of Palantir's biggest competitive advantages, and now the rest of the AI industry appears to be following suit.
So, why exactly did AI change everything? Well, traditional enterprise software could often be deployed with fairly standard implementation playbooks. AI isn't working that way. Every customer has different data, different security requirements, different governance policies, different business processes. >> >> A foundational model by itself isn't creating business value anymore. The value is coming from connecting that model to the enterprise systems and teaching it how the organization actually operates.
That work requires engineers, and not just software engineers. Ones who can sit with customers to understand the business, build solutions, and continuously define them. That's what forward deployed engineers do. One of the reasons that the role is getting so much attention is because it doesn't fit neatly into one traditional IT job, right? So, an FDE might build an AI agent, connect an application, write production code, fine-tune prompts and workflows, work with security teams, solve infrastructure issues, meet directly with executives, and help define entirely new use cases within a customer.
That's equal parts engineer, consultant, solutions architect, and customer success leader. It's a rare skill set. Maybe if you're a channel partner, it's probably ringing a couple bells. This is largely the work that you do to support your customers every day. Now, at first glance, this might seem like vendors are starting to bring services in-house, but I actually think this is creating a huge opportunity for the channel moving forward. >> >> Here's why.
Every major vendor might want FDEs at scale, but there aren't going to be enough of them. Amazon alone is hiring thousands, and then if you multiply that across the rest of the big names, Microsoft, Google Cloud, Oracle, OpenAI, Anthropic, IBM, not to mention all of the AI startups entering the market, demand is exploding and there just simply aren't going to be enough people to hire in-house to do that work. Eventually, or right now, they need partners who can deliver that expertise.
So, let's think about how the channel has evolved over the last 20 years. Many partners started by selling hardware. Then they became infrastructure experts, then that led to cloud consultancies, then that gave way to the rise of an MSP. Now, many are taking the next step and becoming an AI advisor. That next step after that might be building forward deployed engineering capabilities inside your organization. That means hiring people to work directly with customers if you don't already have them, develop AI workflows, connect enterprise data, deploy the AI agents, build the automations, and continuously improve those systems once they go live.
The much higher business value than simply reselling the licenses for the tech itself, and it fits pretty neatly into most MSP models that already exist across other technology types like security and infrastructure. So, what should partners be doing? Well, if you're a solution provider, I'd be asking yourself three questions. First, do we have people who can actually build AI solutions, not just demo the products? Second, can we integrate AI into our customers' existing environments?
And if you're already doing that, are you doing it well and at scale? And third, are we positioning ourselves as long-term AI advisors or one-time implementation partners? Because the market seems to be heading and rewarding the long-term advisory solutions practice >> >> much more than a one-time implementation model's going to work moving forward. So, let's recap. Forward-deployed engineers aren't just another trendy job title. They're a signal that enterprise AI is becoming deeply customized and embedded into every part of an organization.
Customers don't just want software, they want outcomes. And outcomes require people who understand technology and business equally well. Whether those people work for AWS, OpenAI, Anthropic, or your local MSP, may matter less in the long run than one simple fact. The companies that can successfully deploy AI, not just sell it, are going to have a significant advantage over the next decade. And that could be you. Or it could be your competitor. Curious what you think.
Will forward-deployed engineers become a standard role inside channel organizations or is there something else? >> >> An evolution of the model? Or maybe you think that this all just sounds exactly like what you do now and the title doesn't matter nearly as much as whether your customers ultimately benefit. Let me know in the comments, email us at news@channelinsider.com if you'd like to share your perspective. And for more channel analysis, you can subscribe to Channel Insider wherever you saw this video or by heading to our website and subscribing to our weekly newsletter. For Channel Insider, I'm Victoria Durgan.
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