Amazon Web Services (AWS) is expanding its investment in forward-deployed engineering as enterprise demand grows for AI implementations that move beyond experimentation and deliver measurable business results.
Through a dedicated engineering organization and new technical training pathways for partners, AWS is working to develop the specialized skills needed to bring AI applications into production.
The approach could create new opportunities for systems integrators and other IT service providers, but leaders are also warning against “FDE washing,” as companies rebrand traditional consulting engagements without delivering the engineering capabilities and outcomes that define the model.
Forward-deployed engineers create new opportunities for AI partners
For partners, the emerging model represents more than another technical specialization. It could fundamentally change how the channel engages customers, delivers AI projects, and how partners differentiate services.
Rohan Karmarkar, managing director of Partner Solutions Architecture at AWS, told Channel Insider that forward-deployed engineering reflects a significant shift away from traditional consulting engagements.
“These are actual engineers who are working in customers’ environments, and they are building and unlocking AI use cases on real production or real customer data,” Karmarkar said.
Why enterprise AI deployments need specialized engineering
Generative AI has dramatically lowered the barrier to building prototypes. But translating those experiments into reliable enterprise applications requires capabilities that many organizations still lack.
“With AI, as you know, anybody can now build,” Karmarkar said. “Even non-technical personas are able to quickly build a prototype or bring an idea to life.”
“But taking that prototype, an idea that you’ve built into production, requires real engineering capabilities.”
AWS typically structures FDE engagements around teams of four to six professionals combining domain expertise, customer knowledge, and engineering skills.
AWS established its own FDE organization in June and supports AWS-led, partner-led, and joint customer engagements. The company has also introduced technical training pathways designed to help partners develop the engineering capabilities required for production AI deployments.
For partners, the opportunity is to move beyond advisory services and proofs of concept toward implementation work directly connected to business outcomes.
“How do customers really prove that the ROI is there in a few weeks, not months and years after they’ve spent a lot of money?” Karmarkar said. “That’s where I think the FDE engagements have their sweet spot.”
AWS warns partners against ‘FDE washing’
The growing popularity of forward-deployed engineering has also raised questions about whether companies promoting FDE capabilities can actually deliver on them.
Karmarkar said AWS has developed an internal term for the trend: “FDE washing.”
“Existing engagements are called FDE engagements because it’s a good new branding exercise,” he said.
“But for us, FDE’s got a very specific definition and has very specific outcomes that you want to achieve as a part of that engagement.”
The warning holds significant weight across the industry, as more companies invest heavily in FDE programs. In 2026 alone, demand for FDEs is expected to increase by 2,100% according to a C&T study based on survey results from enterprise hiring executives.
It’s also important to remember the model isn’t new. Palantir has leveraged forward-deployed engineers in its offerings for years, before the AI-related surge in demand the market is currently facing.
New AWS training pathways target production AI skills
In October, AWS introduced three technical learning pathways designed to help partners develop those capabilities.
The pathways address grounding AI agents in enterprise data, orchestrating agents across tools and workflows, and proving their reliability through evaluation, observability, security controls, and human oversight.
The training also includes hands-on assessments through which engineers can demonstrate their capabilities and earn credentials.
For AWS, those credentials are intended to help customers identify partners with the technical expertise necessary to deliver production-ready AI systems.
How forward-deployed engineering could reshape partner services in 2027
Karmarkar believes forward-deployed engineering will become an increasingly important capability for many systems integrators, although not necessarily every partner, as AI adoption matures.
“I don’t see FDEs as a thing that’s just a point in time, and over time it’s going to go away,” he said. “I think it’s there to stay.”
The opportunity extends beyond individual deployments. As partners complete engagements, they can develop reusable connectors, frameworks, and implementation patterns that accelerate subsequent projects.
Karmarkar also sees partners playing a larger role as enterprises establish shared AI platforms, governance models, and security controls.
“Partners have started to play a lot bigger role in rolling out these platforms and building the right foundations for scaling,” he said.
For systems integrators and other partners, the shift could change how AI engagements are staffed, priced, and delivered. Partners that can combine specialized engineering talent with reusable implementation frameworks may be better positioned to win production deployments and expand their relationships with enterprise customers.
The challenge heading into 2027 will be proving those capabilities translate into measurable results, rather than simply adopting the FDE label.
READ MORE: Salesforce is one of many other companies that have also formed FDE programs for partners and customers.