$9B +
AI vendor bet
OpenAI, Anthropic, AWS, and Microsoft launched FDE businesses in 2026.
Source: CNBC, TechCrunch
Learn More About Our Company
Integrate Generative AI into your company

Transforming Banking with Cloud, Low-Code & Strategic Partnerships.

Move AI from pilots to production without losing control

Engineers work directly with business stakeholders to turn complex business problems into working solutions.

Built and taught by Xebia’s Forward Deployed Engineers (FDEs), who take AI into production for clients. The program develops engineers who stay accountable for whether the AI works after launch.
$9B +
AI vendor bet
OpenAI, Anthropic, AWS, and Microsoft launched FDE businesses in 2026.
Source: CNBC, TechCrunch
729%
The hiring rush
Rise in FDE job postings, year over year, April 2026.
Source: Indeed, via Business Insider
$173,816
The cost to hire
Median advertised FDE salary across 1,000 postings.
Source: Bloomberry
A Forward Deployed Engineer works where business, customer, consulting, engineering, and AI meet. They combine strong technical capability with business understanding and customer orientation, and they use that combination to move a problem from first understanding to a deployed solution in a real environment, not a demo.
Taking unmapped situations to guide business stakeholders through the process to achieve buildable outcomes. Unlike requirements gathering, there's no spec to read
Building the parts that turn a prompt into a working AI-powered application: retrieval, evaluation, and deployment.
Owning the business side directly to quantify the returns, sizing effort and risk, and holding the roadmap.
Built by practitioners who engineer and deploy technology in complex enterprise environments, Xebia’s FDE curriculum goes further, developing the technical, business, and customer-facing capabilities required to turn AI potential into working solutions.
Xebia’s FDE training curriculum builds a new capability designed for real-world impact. Every path ends the same way. Your team gets an engineer who owns the business outcome, not just the code. Choose the track or set of tracks that best aligns with your team’s goals.
Take AI-enabled solutions into production inside complex enterprise environments.
Build and integrate applications using cloud, containers and modern engineering practices.
Connect services and systems; understand CI/CD and the path from code to production.
Work with data ingestion, lakehouse pipelines and the platforms that support AI.
Understand data streaming, operationalizing ML workflows and managing data responsibly.
Use AI-enabled development workflows to accelerate software engineering.
Learning paths: Software Development / Engineering | Data & AI
Platform options: Platform-agnostic | Azure | AWS | Google Cloud
Build and deploy production-ready solutions in complex enterprise environments.
Build, deploy and operationalize AI solutions for real customer problems.
Understand GenAI applications and workflows in which AI agents use tools to complete tasks.
Build applications that retrieve relevant information and use it to generate grounded responses.
Connect AI components to APIs, applications and enterprise workflows; deploy solutions.
Assess output quality and test AI solutions systematically.
Address safety, privacy, access control and responsible use of AI.
Platform-agnostic: Docker, Kubernetes, Terraform, Airflow/Dagster, dbt and open-weight models.
Cloud-specific: Azure | AWS | Google Cloud
Build and demonstrate deployed, evaluated AI solutions.
Translate challenges into well-defined problems, solutions, and business outcomes.
Understand the industry context, business workflows and operational needs.
Explore customer challenges, clarify requirements and frame the problem to solve.
Define success measures and connect solution choices to business impact.
Work with customers to align on needs, expectations and practical solutions.
Build shared understanding across business and technology stakeholders.
Learning journey: In development
Bridge business needs and technology solutions through domain-led problem solving.
Built by practitioners who engineer and deploy technology in complex enterprise environments, Xebia’s FDE curriculum goes further, developing the technical, business, and customer-facing capabilities required to turn AI potential into working solutions.
Written by the people who build AI systems.
Distinct journey based on the capabilities your team needs to build.
Learning builds from your team’s existing capabilities toward applied FDE skills
Practical scenarios, projects, and real engineering challenges.
Adaptable to your enterprise academies, transformation programs, and engineering teams.
Designed to leave your organization with a durable internal capability.
Xebia brings together 25 years of engineering and enterprise delivery with a long track record of developing tech talent.
Our trainers also put these capabilities to work in client environments.
Building and modernizing software since 2001.
Xebia Academy's track record across tech skills.
From FDE program participants.
We adapt tooling to your cloud and AI ecosystem
Practice is matched to your industry and governance.
Get started
Tell us where your team is today, and we'll map the right entry point
across the three tracks.
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