8 Sources
[1]
Amazon launches new $1 billion FDE org, following OpenAI and Anthropic
As companies struggle to integrate AI, they're increasingly ready to bring in outside help -- and service providers are launching new purpose-built groups to make sure they get it. On Tuesday, Amazon Web Services launched a new internal organization for AI-focused forward-deployed engineers. Engineers on the new team will embed within companies to deploy purpose-built agents, focusing on fast engagements and customer self-sufficiency. In a post announcing the new org, AWS VP of Frontier AI Francessca Vasquez emphasized that the org would do more than build and maintain requested systems. "Customers leave AWS FDE deployments with both new solutions and new engineering capabilities," the announcement reads. "Along with agentic systems running in their own AWS environment, they gain lasting AI skills, workflows, and patterns they can use to innovate independently." Amazon says $1 billion will be committed to the new org, although the figure represents internal Amazon resources rather than a joint venture or conventional investment. Pioneered by Palantir, the forward-deployed engineer (FDE) model has become increasingly popular as a way to manage AI deployments. In a typical FDE system, an engineer from the contracting company (in this case, AWS) works for the client temporarily while the system is being established, allowing them to respond directly as internal opportunities or challenges emerge. In the FDE model, much of the relevant technology can be reused between deployments, while still being tailored to the specifics of each company's needs and workflows. It also gives the client company an influx of expertise and puts primary responsibility for the deployment in the hands of the contractor. The biggest downside is the labor involved, since it means maintaining a full corps of FDE engineers to install and maintain the company's technology. Both OpenAI and Anthropic have launched their own FDE joint ventures in recent months, valued at $4 billion and $1.5 billion, respectively. In those two cases, the AI labs were paired with private equity firms, which provided both the capital to launch and connections with client corporations in their portfolios.
[2]
Amazon's AWS commits $1 billion toward new unit for embedded AI engineers
SAN FRANCISCO, June 30 (Reuters) - Amazon (AMZN.O), opens new tab said on Tuesday it is creating a new division under its Amazon Web Services cloud unit employing so-called forward-deployed engineers who embed with customers to help them more quickly and efficiently adopt artificial intelligence software. The company is committing an initial $1 billion to the initiative with the goal of sending five to six pods of engineers to customers for 45-day periods, said Francessca Vasquez, AWS vice president of frontier AI engineering and services. "We have a ton of demand for customers who are asking for our help to really drive agentic AI patterns in their workflows," said Vasquez, in an interview prior to the announcement. Forward-deployed engineers are versatile workers who embed directly alongside clients, navigate internal politics and write production-grade code to help make models deliver results. Amazon is a bit late to the party. Palantir Technologies has had its own forward-deployed engineering unit for well over a decade and others such as Salesforce, Anthropic and Google Cloud also offer their own versions of the service. Forward-deployed engineering is a rare bright spot among tech companies that have been cutting jobs amid the rapid expansion of AI. Box CEO Aaron Levie said in a LinkedIn post in May that forward-deployed engineers are "about to become one of the most in-demand jobs in tech." And from 2023 to 2025, demand for forward-deployed engineers and similar roles grew 42-fold, according to a LinkedIn report earlier this year. AWS said it planned to have "thousands" of employees in the new unit, without offering specifics, and would hire from outside the company to fill some roles as well as move others internally. Amazon has cut over 30,000 corporate jobs since October. Amazon announced the new unit as part of a two-day customer event in Washington, where it is expected to make additional announcements around government cloud offerings. Success for the new unit would be measured in how quickly customers can develop a new product or learn new skills with the help of Amazon's forward-deployed engineers, said Vasquez. "We want to make sure that these customers get value in faster durations than what they've traditionally seen in project-based activity," she said. Amazon said initial customers include the National Basketball Association and Ricoh, an electronics company. Reporting by Greg Bensinger; Editing by Sanjeev Miglani Our Standards: The Thomson Reuters Trust Principles., opens new tab * Suggested Topics: * Artificial Intelligence Greg Bensinger Thomson Reuters Greg Bensinger joined Reuters as a technology correspondent in 2022 focusing on the world's largest technology companies. He was previously a member of The New York Times editorial board and a technology beat reporter for The Washington Post and The Wall Street Journal. He also worked for Bloomberg News writing about the auto and telecommunications industries. He studied English literature at The University of Virginia and graduate journalism at Columbia University. Greg lives in San Francisco with his wife and two children.
[3]
AWS puts $1 billion into new AI unit to embed engineers with customers, joining growing wave
Amazon Web Services on Tuesday announced it is investing $1 billion in a new Forward Deployed Engineering unit that will help its customers build and roll out artificial intelligence systems. A forward-deployed engineer, or an FDE, is an employee who is embedded directly within a different business to try and accelerate a technical transformation. Defense contractor Palantir coined the term more than a decade ago, but it's seen a resurgence among software vendors looking to boost adoption by taking talent directly into clients' facilities. Leading model developers, including OpenAI and Anthropic, announced their own FDE companies earlier this year, in partnership with banks, private equity and consulting firms. Now, AWS is looking to carve out its own piece of the market. "We've had capabilities over the years, but structurally this is like getting everybody together in one business unit with a common rubric of deployment," Francessca Vasquez, AWS' vice president of frontier AI engineering and services, said in an interview. "It's the first time we're doing it in that way." Amazon, which is the top cloud provider by revenue, is the first hyperscaler to announce this kind of initiative. Vasquez said AWS' new unit will be seeded with "thousands" of FDEs. An initial pod of roughly five or six engineers will be embedded within an AWS customer at a time, and those employees will also work alongside AI agents, which are tools that can independently complete tasks on behalf of their users. AWS said in a blog post that its FDE embeds will partner closely with customers' business, engineering and security staffers, and they'll look to leave behind self-sufficient teams with new solutions and capabilities in a matter of weeks. "The currency that the customers are always talking about right now is speed," Vasquez said. "We do see FDE being a choice for customers who are looking for accelerated value back to their stakeholders, their customers, their executive teams."
[4]
AWS puts $1bn into forward-deployed AI engineers
Amazon is the first cloud giant to copy the embedded-engineer playbook Palantir built and OpenAI and Anthropic have since adopted, funding the unit entirely off its own balance sheet. Amazon Web Services is committing $1bn to embed its own engineers inside customer companies. It is the first cloud giant to copy a playbook that Palantir built and that OpenAI and Anthropic have since adopted. Amazon Web Services said on June 30, 2026 that it would pour $1bn into a new Forward Deployed Engineering unit. The team's job is to help customers build and run artificial intelligence systems. Francessca Vasquez, the company's vice-president of frontier AI engineering and services, set out the plan in an interview with CNBC. Her pitch came down to one word: speed. A forward-deployed engineer, or FDE, is a technical specialist who works from inside a client's business rather than from the vendor's own offices. Palantir coined the term more than a decade ago. The idea has since spread to software firms that want faster adoption of their tools, and it now sits at the centre of the race to sell enterprise AI. What AWS is actually building The new unit will start with what AWS calls "thousands" of engineers. It will send them out in small pods, each with five or six people, embedded inside a single customer at a time. Those engineers will also work alongside AI agents, the software tools that can carry out tasks on their own. The pods are meant to move fast. AWS said in a blog post that its engineers would sit with a customer's business, engineering, and security teams, then hand back a self-sufficient team within weeks. "The currency that the customers are always talking about right now is speed," Vasquez said. She added that the model suits firms chasing quick returns for their executives and stakeholders. Vasquez framed the launch as a step change rather than a brand-new skill. "We've had capabilities over the years, but structurally this is like getting everybody together in one business unit with a common rubric of deployment," she said. "It's the first time we're doing it in that way." Copying a model OpenAI and Anthropic already chose AWS is late to a party its own partners started. In May 2026, Anthropic set up an AI services company with Blackstone, Hellman & Friedman, and Goldman Sachs to help mid-sized firms roll out its Claude models. Days later, OpenAI launched its deployment company with TPG, Advent International, Bain Capital, and Brookfield, among others. Those rivals built their deployment arms as joint ventures, leaning on outside investors and consulting partners. AWS is taking a different route. It is funding the unit from its own balance sheet, with no partner firms attached. Google has made its own move too, with a $750mn partner fund aimed at agentic AI deployments. Amazon has spent billions of dollars backing both Anthropic and OpenAI. It has also been clear about competing with them directly in places. An AWS spokesperson said the company still expected to work with the FDE arms of both labs, and promised more detail on its partner programmes soon. AWS has separately agreed to sell OpenAI's models after Microsoft's exclusivity lapsed. Why a cloud giant wants bodies on the ground The logic is about adoption, not headcount for its own sake. Companies have bought plenty of AI tools. Many have struggled to turn them into working systems. By placing engineers inside the customer, AWS hopes to close that gap and tie clients deeper into its cloud. The move also shows how AWS plans to defend its lead. Amazon is the biggest cloud provider by revenue, and it is the first hyperscaler to commit to an FDE unit at this scale. The bet is that hands-on help, not just cheaper compute, will decide who wins enterprise AI. Amazon has also pushed customers toward cheaper AI options as model costs climb. Not everyone will read the spend as a sure thing. Investors have grown wary of the huge sums flowing into AI, and they keep asking when the returns will land. A $1bn unit staffed by costly engineers adds to that bill. AWS is betting the outlay pays for itself in stickier, larger cloud contracts. The proof will sit in next year's numbers, not in the launch. There is a hiring story here as well. AWS wants thousands of engineers for the unit at a time when AI is eating into entry-level work. The roles it is creating are senior, client-facing, and hard to automate. That is a notable contrast with the junior jobs the same technology is removing. The customers already signed up AWS named several early adopters. They include the Allen Institute, the National Basketball Association, the National Football League, and Ricoh. Vasquez said the next wave would come from heavily regulated industries that hold large, varied datasets. Those are the firms with the most to gain from faster deployment, and the most to lose from getting AI wrong. For now, the move sharpens a question hanging over the whole sector. Businesses have spent heavily on AI and seen patchy results. Whoever turns that spending into working systems fastest will pull ahead. AWS has just bet $1bn that the answer is people, sent to sit at the customer's desk.
[5]
AWS launches forward-deployed engineering team to speed enterprise agentic AI adoption
AWS launches forward-deployed engineering team to speed enterprise agentic AI adoption Amazon Web Services Inc. said today it's rolling out a new dedicated organization to bring agentic artificial intelligence systems, built on the same technology, to customers by embedding engineers in enterprise customer operations. Backed by a $1 billion investment, the dedicated Forward Deployed Engineering department will bring what the cloud computing giant calls AWS frontier teams into the field. These are small groups of experienced experts who work directly within enterprise companies, along with AI agents, to customize, wire up and educate customers. Agentic AI is at the forefront of the company's new approach, Francessca Vasquez, vice president of Frontier AI Engineering and Services, told SiliconANGLE in an interview. Agents are changing the business landscape in ways never seen before, and customers are caught in the turbulence, trying to keep up with the transformation. "It's like the next inflection point," Vasquez said. "It's not just workloads and use cases. It is really taking a true business workflow end-to-end." Machine learning has quietly underpinned many business operations for years, but the advent of generative AI has rapidly changed the game. Its emergence and evolution have created a demand for enterprise experimentation ever since OpenAI Group PBC introduced ChatGPT to the mainstream. Since then, it has shifted from question-and-answer chatbots to fully autonomous agents capable of fulfilling complete business-oriented goals with humans in the loop. The wake of this transformation has only accelerated already existing desires to tighten software and product development workflows, allowing companies to take ideas to production faster than ever before. Vasquez said that customers came to AWS with a pain point of trying to condense two- and three-year transformation projects into something more manageable for the current fast-paced business environment. According to the company, its FDE teams can compress what took months into days using agentic AI, and when they complete a task with a verifiable outcome, they leave behind the same intelligent tools they used to build it. "The new currency of value is speed," Vasquez said. "Ideate on in 45 minutes, validate that idea in 45 hours, and then ship something within your workflow of value in 45 days." This 45/45/45 work metric permeates the FDE approach. Although the objective is to complete a single package within the 45-day window, Vasquez noted that it's fine if it arrives sooner. Sometimes teams remain on site for multiple sprints, either to iterate on a design or to move on to wire up multiple departments or use cases that cannot be completed readily in parallel. Digital gold into operational infrastructure The era of generative AI showed the tech industry that data, especially the bespoke business data and constant information generated by the people working there, is akin to "digital gold." It's the beating heart of enterprise operations, holding everything together, and it's also required to make AI agents smarter and more accurate. After an FDE team lands and completes a sprint, they leave behind more than just an app, Vasquez said. The objective is to build the company's semantic layer. The idea of a semantic layer, knowledge graph, or internal ontology has become the motto of agentic transformation; it is the core of what could be called a "system of intelligence" for agents, by building a network of relationships among software, business knowledge, processes and structure. "It's a customer's ontology of their information, which for many organizations is gold," Vasquez explained. FDE teams provide support alongside the completion of integration and transformation. "Being able to codify elements of that is also super useful for organizations." Customers already using FDE teams on site include a broad variety of technology-oriented industry players. They include the Allen Institute for AI, Cox Automotive Inc., the National Basketball Association, the National Football League and Ricoh Company Ltd. "The NFL has millions of fans who want to consume football content throughout the year, including the offseason," said Gary Brantley, chief information officer of the NFL. "We innovate at the pace and scale needed to meet the high expectations of our fans." Brantley explained that, by using the new FDE paradigm and partnering with AWS, the NFL has been able to spin up new digital experiences, including fan-facing products such as NFL Fantasy AI and NFL IQ. These products allow fans to interact with NFL data in ways that were not immediately plausible before the generative AI and agentic revolution.
[6]
Amazon's AWS commits $1 billion toward new unit for embedded AI engineers
The company is committing an initial $1 billion to the initiative with the goal of sending five to six pods of engineers to customers for 45-day periods, said Francessca Vasquez, AWS vice president of frontier AI engineering and services. Amazon said on Tuesday it is creating a new division under its Amazon Web Services cloud unit employing so-called forward-deployed engineers who embed with customers to help them more quickly and efficiently adopt artificial intelligence software. The company is committing an initial $1 billion to the initiative with the goal of sending five to six pods of engineers to customers for 45-day periods, said Francessca Vasquez, AWS vice president of frontier AI engineering and services. "We have a ton of demand for customers who are asking for our help to really drive agentic AI patterns in their workflows," said Vasquez, in an interview prior to the announcement. Forward-deployed engineers are versatile workers who embed directly alongside clients, navigate internal politics and write production-grade code to help make models deliver results. Amazon is a bit late to the party. Palantir Technologies has had its own forward-deployed engineering unit for well over a decade and others such as Salesforce, Anthropic and Google Cloud also offer their own versions of the service. Forward-deployed engineering is a rare bright spot among tech companies that have been cutting jobs amid the rapid expansion of AI. Box CEO Aaron Levie said in a LinkedIn post in May that forward-deployed engineers are "about to become one of the most in-demand jobs in tech." And from 2023 to 2025, demand for forward-deployed engineers and similar roles grew 42-fold, according to a LinkedIn report earlier this year. AWS said it planned to have "thousands" of employees in the new unit, without offering specifics, and would hire from outside the company to fill some roles as well as move others internally. Amazon has cut over 30,000 corporate jobs since October. Amazon announced the new unit as part of a two-day customer event in Washington, where it is expected to make additional announcements around government cloud offerings. Success for the new unit would be measured in how quickly customers can develop a new product or learn new skills with the help of Amazon's forward-deployed engineers, said Vasquez. "We want to make sure that these customers get value in faster durations than what they've traditionally seen in project-based activity," she said. Amazon said initial customers include the National Basketball Association and Ricoh, an electronics company.
[7]
Amazon Joins Anthropic, OpenAI to Launch AI Consulting Services to Lure Enterprises
And these consultants are deployed as part of an FDE organisation with massive budgets and the sole task of delivering enterprise customers to these AI labs seeking to bolster revenues What would you do if your AI solutions are either not achieving the defined outcomes or are costly or possibly a bit of both? You begin a consulting service and call it forward-deployed engineers who can create a need and fulfil it when enterprise CTOs aren't sure. OpenAI did it, as did Anthropic. And now, Amazon Web Services (AWS) has followed suit. AWS launched an internal organisation for AI-focused forward-deployed engineers (FDE) who will embed with companies to deploy custom-built agents that focuses on fast engagements and customer self-sufficiency. "The organization uses agentic AI to build agentic solutions, compressing deployments from months to days," AWS says in a note. AWS VP of Frontier AI Engineer and Services Francessca Vasquez, notes: "Customers have moved past exploring what AI can do; they want to make it core to how they operate. They want to recreate their business processes with agentic AI built in so they can increase productivity and deliver AI-powered products. "I have also heard loud and clear that many customers need expert AI engineers working directly with their teams to help them build and become AI-native organizations. And this is what AWS FDE organisation backed by $1 billion investment would do. "It is agentic-first, it compresses timelines from months to days, and it is designed so customers are self-sufficient when a deployment ends," he says. Customers leave AWS FDE deployments with both new solutions and new engineering capabilities," he says. "Along with agentic systems running in their own AWS environment, they gain lasting AI skills, workflows, and patterns they can use to innovate independently." Readers would recall that the FDE model was pioneered by Palantir and has become popular as a means to manage AI deployments. The format reminds us of the early days of software solutioning where companies specifically formed for the purpose used to cherry-pick from a range of products and solutions to deliver one was customised for a particular enterprise. In the modern version, an engineering from the contracting company like AWS, OpenAI or Anthropic would work on client site temporarily while supporting the establishment of the system and being part of a knowledge transfer process. These FDEs would respond directly as challenges emerge or new opportunities are created, thus making it a win-win for both parties - the enterprise gets the expertise and learns and the provider gets business revenues. Moreover, the relevant technology can be reused between deployments while still being customised for specific requirements within a division or around workflows. The customer also ends up getting the expertise requirement for future deployments, though in the initial stage the primary responsibility rests with the contractor. Interestingly, the first ones off the block with similar ventures were OpenAI and Anthropic who brought new FDE joint ventures in May amidst concerns around enterprise revenue growth and the overall cost of AI infrastructure not matching up. The companies invested around $4 billion and $1.5 billion in the ventures that paired them with private equity companies that provided both capital and their customer lists. Francessca Vasquez said AWS Partners will play an important role here, contributing model expertise, industry knowledge, and complementary skills to ensure the right engineers are available to customers. We are investing in partner training, tools, and resources to accelerate AWS FDE engagements. "We've been building AI solutions for customers since 2017 -- and for the past three years, the AWS Generative AI Innovation Center's engineers have worked on thousands of customer solutions," he says adding "now, as customers ask us to dive deeper with them, go beyond individual use cases, and help grow their AI capabilities, we're expanding our commitment to this approach."
[8]
AWS to invest $1 billion in AI engineering deployment program By Investing.com
Investing.com -- Amazon Web Services announced Tuesday a new Forward Deployed Engineering organization backed by a $1 billion investment to embed AI experts directly with customers. The AWS FDE program will place thousands of engineers at customer sites to develop and deploy agentic AI solutions. The company said deployment timelines will be reduced from months to days through the use of agentic AI tools. AWS said the program aims to help customers integrate AI into their core business operations. The engineers will work alongside customer business, engineering, and security teams to build production AI systems using customer data and governance processes. The program is designed to leave customers able to operate independently after deployments are completed. AWS said the embedded engineers include team members who build AWS AI services. Several organizations are already working with AWS FDE teams, including the Allen Institute, Cox Automotive, the National Basketball Association, the National Football League, Ricoh, and Southwest Airlines. The announcement comes as businesses move beyond testing AI capabilities and seek to make the technology central to their operations, according to AWS. This article was generated with the support of AI and reviewed by an editor. For more information see our T&C.
Share
Copy Link
Amazon Web Services launched a new Forward Deployed Engineering organization backed by a $1 billion investment to embed engineers directly within customer companies. The unit will deploy small pods of five to six engineers for 45-day periods to help businesses rapidly build and implement agentic AI systems, following similar moves by OpenAI and Anthropic.
Amazon Web Services announced on Tuesday the creation of a dedicated Forward Deployed Engineering unit, backed by an AWS $1 billion investment, to help companies navigate AI integration challenges
1
2
. The initiative represents a shift in how the leading cloud computing provider approaches enterprise agentic AI adoption, placing embedded AI engineers directly within customer organizations to accelerate AI system deployment3
.
Source: Reuters
Francessca Vasquez, AWS vice president of frontier AI engineering and services, emphasized that the new unit focuses on speed as its primary currency. "We have a ton of demand for customers who are asking for our help to really drive agentic AI patterns in their workflows," Vasquez said in an interview
2
. The organization plans to deploy thousands of engineers who will work alongside purpose-built AI agents to compress transformation timelines from months into days5
.The Forward Deployed Engineering approach involves sending small pods of five to six engineers to embed with customers for 45-day periods
2
. These engineers work directly alongside clients' business, engineering, and security teams, responding to internal opportunities and challenges as they emerge3
. The model allows much of the technology to be reused between deployments while still being tailored to each company's specific needs and workflows1
.
Source: SiliconANGLE
Vasquez outlined what the company calls a 45/45/45 work metric: "Ideate on in 45 minutes, validate that idea in 45 hours, and then ship something within your workflow of value in 45 days"
5
. This framework emphasizes rapid iteration and measurable outcomes, addressing customer demands to condense two- and three-year transformation projects into more manageable timeframes5
.Amazon Web Services becomes the first hyperscaler to announce this type of initiative, though it arrives later than competitors
3
4
. Palantir pioneered the forward-deployed engineer model over a decade ago, and both OpenAI and Anthropic launched their own FDE joint ventures in recent months, valued at $4 billion and $1.5 billion respectively1
. Those AI labs partnered with private equity firms to provide capital and connections with client corporations in their portfolios1
.AWS takes a different route, funding the unit entirely from its own balance sheet with no partner firms attached
4
. An AWS spokesperson confirmed the company still expects to work with the FDE arms of both Anthropic and OpenAI4
. The move signals how cloud providers plan to defend market position through hands-on support rather than just cheaper compute4
.Related Stories
Beyond deploying systems, AWS emphasizes that customers leave engagements with new engineering capabilities and lasting AI skills
1
. The FDE teams help build what Vasquez describes as a company's semantic layer or system of intelligence—a network of relationships among software, business knowledge, processes, and structure5
. "It's a customer's ontology of their information, which for many organizations is gold," Vasquez explained5
.Initial customers include the National Basketball Association, NFL, Ricoh, Cox Automotive, and the Allen Institute for AI
2
5
. Gary Brantley, chief information officer of the NFL, noted that the partnership enabled the league to spin up new digital experiences including NFL Fantasy AI and NFL IQ, allowing fans to interact with NFL data in previously implausible ways5
.The Forward Deployed Engineering model represents a bright spot in tech employment as demand for these roles grew 42-fold from 2023 to 2025, according to a LinkedIn report
2
. Box CEO Aaron Levie noted in May that forward-deployed engineers are "about to become one of the most in-demand jobs in tech"2
. This contrasts sharply with Amazon's recent corporate job cuts of over 30,000 positions since October2
.
Source: TechCrunch
Vasquez indicated that the next wave of customers would likely come from heavily regulated industries holding large, varied datasets—firms with the most to gain from faster deployment and the most to lose from implementation failures
4
. Success for the unit will be measured by how quickly customers can develop new products or learn new skills with AWS support, rather than traditional project timelines2
. The bet is that this substantial investment in senior, client-facing roles will pay for itself through stickier, larger cloud contracts as AI adoption becomes a competitive necessity4
.Summarized by
Navi
[3]
[4]
28 Apr 2026•Technology

17 Jul 2025•Technology

05 Mar 2025•Technology

1
Policy and Regulation

2
Technology

3
Science and Research
