Amazon Web Services (AWS) announced on June 30 it will invest $1 billion in a new Forward Deployed Engineering (FDE) unit dedicated to accelerating AI system deployment by embedding engineers directly with customers [1, 2, 3].
The FDE teams will work alongside customer business, engineering, and security staff to build self-sufficient AI teams within weeks, rather than months [1, 3]. Initial deployment pods will range from 5 to 6 engineers who typically stay embedded with a customer for about 45 days [1, 2]. AWS plans to expand the unit to thousands of forward deployed engineers, recruiting both internally and externally [1, 2].
AWS is the first hyperscale cloud company to create a dedicated FDE unit focused solely on AI adoption. The teams help customers connect enterprise data into governed knowledge graphs within AWS environments, enabling AI applications while ensuring strict data governance [3]. Customers such as the NFL, Allen Institute, Cox Automotive, NBA, and Ricoh are already working with AWS's FDE teams [3].
"We have a ton of demand for customers who are asking for our help to really drive agentic AI patterns in their workflows," AWS VP Francessca Vasquez said. She added, "The currency that the customers are always talking about right now is speed. We do see FDE being a choice for customers who are looking for accelerated value back to their stakeholders, their customers, their executive teams" [1, 2]. Vasquez emphasized the goal to deliver value faster than traditional project timelines typically allow [2].
Forward deployed engineering roles have surged in demand, growing 42-fold from 2023 to 2025, amid widespread tech layoffs [2]. Palantir coined the term more than a decade ago and has operated FDE units for years. Companies including Anthropic, Salesforce, and Google Cloud also provide embedded engineering teams [1, 2]. In May 2026, Anthropic launched its own AI services company using forward deployed engineers with partners such as Blackstone and Goldman Sachs [1].
AWS aims for its FDE unit to speed AI project timelines from months to days [3]. The first engineers will begin embedding with customers immediately following the announcement.
