Paid From Day One
Intensive AI Engineering
Real Career Pathway
Highly Selective
Built by Aleph.
Trusted by leading organizations.
Aleph selects, trains, and deploys technology professionals into some of the world's most demanding enterprise environments.
SGTech Workforce Transformation Award 2025
What is a Forward Deployed Engineer?
An FDE doesn't just build AI in isolation. They work closely with organizations to understand complex problems, design solutions, integrate AI into existing systems, and take those solutions from idea to production.
Understand
Translate complex business problems into technical requirements.
Build
Develop AI applications, integrations, and workflows.
Deploy
Bring solutions into real enterprise environments.
Own
Work with stakeholders from discovery through delivery.
Why FDE is becoming one of AI's most important roles
Companies have spent the last few years experimenting with AI. The next challenge is making it work inside real organizations. That takes engineers who can understand business problems, build technical solutions, and deploy them into complex enterprise environments. As AI moves from experimentation to implementation, demand is growing for engineers who can bridge technology, customers, and real world deployment.
800%
Growth in Forward Deployed Engineer job postings from January to September 2025, as companies invested in taking AI into production.
Source: Financial Times, September 2025
95%
Share of enterprise AI pilots that stall. Many initiatives struggle with integration, deployment, and adoption, the gap FDEs are designed to close.
Source: Forbes, May 2026
1,000
Forward Deployed Engineers in the FDE organization Salesforce announced to help customers turn AI into working enterprise solutions.
Source: Salesforce, 2026
Everything is built around
what you become.
You are not joining another course. You are joining a selective employment pathway designed to make you useful in real AI deployment environments.
Engineer with AI depth
Go beyond AI tools and learn how AI systems are actually built and deployed.
Enterprise ready
Learn how to work within complex infrastructure, security, and business environments.
Customer facing
Build the communication and problem solving skills needed to work directly with stakeholders.
Deployment ready
Develop the technical depth to take AI beyond proof of concept.
From engineer to Forward Deployed Engineer
Build on the engineering experience you already have and develop the AI, deployment, and customer facing skills needed to move into one of tech's emerging roles.
Today
Roles
Next Steps
Role
For engineers with around two to three years of experience who need a stronger foundation before progressing into forward deployment.
Role
For experienced engineers with five or more years who are ready to combine engineering, AI, solution design, and customer delivery.
Where it can take you
As you gain deeper technical expertise, deployment experience, and customer ownership, your career can progress into senior engineering, architecture, and technical leadership roles.
Roles
Two pathways.
One shared journey.
Forward Integration Engineers start first with four weeks of engineering foundations. Forward Deployed Engineers then join the cohort for the shared 10 week program.
Foundations
FIE Training starts here.
WEEKS 1 to 4
WEEK 1-2
Engineering: Python for production, not scripts; testing, linting, and Git practice; SDLC, secrets, and CI/CD basics
WEEK 3-4
Enterprise environment: Network architecture and the OSI model; DNS, firewalls, ACLs, NAT, and routing; Layer 1 to 3 troubleshooting
Services and Infrastructure
FDE Training starts here.
WEEKS 5-7
WEEK 5-6
Applied AI Foundations: LLMs, prompting, model APIs, embeddings, RAG, and building AI powered applications. (FDE starts here)
WEEK 7
Deploy: AWS EC2, S3, IAM, Lambda, and VPC; Docker images, Compose, and Kubernetes; Terraform and Ansible
Applied AI
WEEKS 8-11
WEEK 8-9
AI development: Data analysis and preparation; LLM APIs, Hugging Face, and local models; RAG, tools, memory, and evaluation
WEEKS 10-11
Tooling and serving: MCP and tool or context integration; AI assisted development and prompt work; vLLM, Triton, SageMaker, and NIM
Production and Capstone
WEEKS 12-14
WEEK 12-13
Run it: Monitoring, observability, and AI security; Splunk, SPL, dashboards, and alerting; correlation searches and SIEM use cases
WEEK 14
Hand it over: Deploy a production LLM application; architecture diagram and runbook; final presentation and handoff
The stack you will learn to use
Build practical experience across the languages, cloud platforms, AI tools, deployment systems, and security technologies used in real enterprise environments.
Language and code
Python
Flask
GitOps
SQLCloud and infrastructure
AWS EC2
S3
IAM
Lambda
VPC
Terraform
AnsibleContainers and delivery
Docker
KubernetesAI development
LLM APIs
Hugging Face
Ollama
GradioAgents and tooling
MCPServing and deployment
vLLM
NVIDIA Triton
AWS SageMakerNVIDIA NIMMonitoring and security
SplunkChoose the path that matches your experience
Both tracks lead toward customer facing AI deployment work. Your experience determines where you begin and how much ownership you take during the cohort.
2 to 3 Years Required
Forward Integration Engineer
Apply if you:
Have two to three years of professional engineering experience; work in software, backend, cloud, data, ML, DevOps, or support engineering; are comfortable in Python and have worked in a production codebase; want AI to be the job rather than something you read about on weekends.
In the cohort
Build under the guidance of engineers who have shipped AI in production, own real components of the capstone, and present your own work at demo day.
5+ Years Required
Forward Deployed Engineer
Apply if you:
Have five or more years of professional engineering experience; have owned a complex technical project from start to delivery; work as a senior or staff engineer, architect, consultant, or engineering manager; can hold a technical conversation with a customer without a manager in the room.
In the cohort
Lead technical workstreams, own customer facing conversations, shape solution design, and mentor associates rather than repeat fundamentals you already have.
Both tracks require
Not sure which pathway fits you? Apply to the FDE Program and our selection team will assess the right entry point based on your experience.
ApplySelected for skill-set and potential.
Trained for impact. Deployed where it matters.
Many career transition courses leave you to find a job on your own after you finish. Here, you are a full time employee from day one, and you train toward a placement with a partner organization.
Select
We assess your technical foundation, problem solving ability, and potential to succeed in demanding enterprise environments.
Train
Join Aleph as a full time employee and complete intensive FIE or FDE training designed around real world AI engineering and delivery.
Deploy
After completing the program, move into client facing enterprise assignments matched to your skills, experience, and deployment requirements.
We invest in your career from day one.
Training is only one part of the experience. You join Aleph as an employee and receive the structure, support, and benefits needed to focus on becoming deployment ready.
Employed from day one
Join Aleph as a full time employee and receive compensation throughout training.
Fully sponsored training
Aleph covers the full cost of your intensive training and development.
Employee benefits
Receive the applicable Aleph employee benefits during your employment.
Expert mentorship
Learn from practitioners across AI, cloud, software, cybersecurity, and enterprise delivery.
Career development
Strengthen your technical delivery, communication, problem solving, and stakeholder skills.
Long term community
Keep learning through Aleph mentors, peers, customer projects, and alumni connections.
Questions worth asking
An FDE works directly with customers to understand complex problems, build technical solutions, integrate them into existing systems, and support deployment and adoption.
No. It is an employment and career development pathway. You are hired first, then trained through intensive practical work in applied AI engineering and enterprise delivery.
Requirements depend on the track. You should have a relevant technical foundation, strong problem solving ability, and the capacity to learn quickly. The FDE Handbook covers eligibility in full.
Yes. You are a paid Aleph employee for all 10/14 weeks of training, not a student. Compensation and benefits are shared with qualified applicants during the process.
Graduates work on Aleph initiatives or customer projects, matched on skills, experience, performance, location, and business need.
Yes. Aleph pays your salary and the full cost of training, so we ask for a minimum service period in return. You will see the exact length, the terms, and the route to permanent conversion or direct employment in writing before you accept anything. Nothing about it is a surprise later.
Yes. The experienced track is built for established engineers moving into AI deployment, technical leadership, and customer facing delivery.
Build AI that moves beyond the demo
Turn your engineering experience into a career deploying AI where it matters.
