Freelance Forward Deployed Engineer
I join your team, work inside your real systems, and take AI from demo to production.
A forward deployed engineer builds inside your environment, not around it: integrations, custom agents, MCP servers, and evals. The work between a promising pilot and a system people actually use. I do this as a freelancer: embedded, fractional, or per project.
What Is a Forward Deployed Engineer?
A forward deployed engineer (FDE) is an engineer who embeds with a customer's team and builds inside their real environment, instead of shipping advice or a generic product from the outside. The role started at Palantir almost two decades ago. The AI wave made it mainstream: OpenAI and Anthropic build whole forward deployed engineering teams, and job postings for the role grew more than 800% in 2025 while the pool of people who can do the job grew about 50%.
The role exists because most AI projects don't fail on model quality. They fail at integration. The demo works, and then it has to talk to a legacy database, pass a security review, respect permissions, and survive real users. Getting through that takes someone sitting inside your systems, not a vendor on the other side of a ticket queue.
I've Been Doing This Work for Years
Most of my client work has had exactly this shape: join the team, learn the domain, wire AI into the systems they already run, and stay until it works. The industry now has a name for it. The work hasn't changed.
What I Actually Do
Systems Integration
Connecting AI to what you already run: databases, internal APIs, auth, and the data pipelines that feed it. This is where most of the time goes, and where most projects stall.
Custom Agents & MCP Servers
Agents that do real work inside your tools, and MCP servers that give them safe access to your systems. Built with your engineers, not around them.
Evals
A test suite for AI behavior: measuring quality, catching regressions, and tracking cost and latency, so "it seems better" becomes a number.
Demo-to-Production Hardening
Monitoring, fallbacks, error handling, permissions, and cost control. The unglamorous work between a pilot and a system people rely on.
Working Inside Your Team
I sit in your standups, your repo, and your Slack. Your engineers see how everything is built and own it when I leave.
Straight Answers for Leadership
Translating fuzzy goals into buildable scope, and progress into terms the business understands. No decks for the sake of decks.
Who This Is For
Your Pilot Is Stuck
The demo impressed everyone months ago and it's still not in production. Something in the middle (data, security, integration) keeps not getting solved.
You Sell AI and Your Customers Need Help
You're an AI product company and every new enterprise deal needs custom deployment work your team doesn't have hands for.
You Need Senior AI Hands, Not a Hire
The work is real but it's a system or two, not a permanent function. You want someone senior embedded now, without running a long hiring pipeline first.
How It Works
1. Embed
We define what production means for this project. Then I join the team: repo access, the real data, the actual constraints.
2. Ship
Short loops inside your environment: integrate as we go, put working software in front of real users early, because that's where the truth is.
3. Hand Off
Your team owns the result: code, documentation, evals, and the knowledge to run and extend it. Success is that you don't need me afterward.
Ways to Work Together
Same work, three shapes. We pick the one that fits the problem.
Embedded Sprint
A focused push on one system: take the stuck pilot and get it into production.
Fractional
A fixed part of every week, ongoing. I work as your team's AI engineer, across projects.
Per Project
A defined build with a defined end: scoped, shipped, handed off.
Where to Go Next
Frequently Asked Questions
What does a forward deployed engineer do?
A forward deployed engineer embeds with a customer's team and builds inside their real systems: connecting AI to existing data and tools, handling the constraints a demo never meets, and staying until it runs in production. The role started at Palantir and is now standard at AI companies like OpenAI and Anthropic.
How is this different from your AI consulting?
Consulting is guidance: we work out what to build and how, and I review the work as it takes shape. A forward deployed engagement means I am inside the team doing the building. If you need advice, start with consulting. If you need the thing shipped, this is the one.
Why hire a freelance FDE instead of hiring full time?
Because the hiring math is hard right now. FDE job postings grew more than 800% during 2025 while the candidate pool grew about 50%, and the US median base salary is around $174K. If the work is a system or two rather than a permanent function, an embedded freelancer gets it shipped without the long hire.
Do you work with AI companies or with companies adopting AI?
Both. For companies adopting AI, I take the pilot that's stuck and get it into production. For AI product companies, I do the customer-side deployment work: integrations, onboarding, and the engineering that turns a signed contract into a live system.
Do you work remotely or on-site?
Both. RZ AI Labs is based in Haifa, Israel, and engagements run remotely or on-site worldwide.
Who will I be working with?
Me, directly. Twenty years of building software from developer to architect, a B.Sc in Computer Science from the Technion, and years of hands-on AI work: agents, MCP servers, and production systems for organizations including Intel, Microsoft, KLA, and Johnson & Johnson.