Fractional Lead AI Engineer
AI Teams Builder
by Ahmed Mostafa
You hired AI engineers. They're shipping demos that work on stage and break in production. I step in for three to six months as the Lead AI Engineer your team is missing — and leave once they can ship without me.
Services
Four ways I help your team ship.
The Lead AI Engineer in the room
When a call needs someone who's shipped this before — architecture choices, hiring loops, vendor selection — I'm the one who makes it and stands behind it. The decisions that stop your project from stalling in committee.
Production-grade AI engineering
A working demo and a production system are different engineering problems. I install the discipline that closes the gap — evaluation frameworks to catch quality regressions, observability to detect model drift, and deployment workflows that keep customer-facing features stable. The industry calls it MLOps.
Level up your engineers
Your team is smart. They just haven't shipped these patterns yet — most engineers haven't. I've spent the last eight years doing exactly that. Weekly 1:1s, code review, and structured teaching on the LLM and agent patterns your roadmap actually needs.
An engagement with an exit
Most consultants want to stay. I want to leave. We agree on scope, milestones, and the handover before we start — and the exit is on the calendar from day one.
Process
From the intro call to the handover.
Six steps. Every engagement runs the same shape — only the dates, the scope, and the success criteria change.
The intro call
30 minutes
You describe the situation — your team, what's working, what isn't, what you're trying to ship. I tell you whether I'm the right fit. No slides, no obligation. If it isn't a fit, I'll say so on the call.
Scoping & agreement
Within one week
If we're a fit, we write the engagement together. Scope, milestones, success criteria, weekly cadence, and the exit date — on paper before either of us signs. You get a fixed monthly fee and a fixed end date.
Week one — the assessment
Days 1 – 5
I join your team. I read your code, sit in your standups, and talk to every engineer 1:1. By Friday, you have a written technical assessment: what's working, what's at risk, the three things we do first.
Lead & enable
Months 1 through 5
I take the Lead AI Engineer seat. Architecture calls, hiring loops, code review, weekly 1:1s, MLOps standards, and the production discipline that turns demos into systems. I'm in your Slack, your sprint reviews, your roadmap calls.
Handover
Final two weeks
One of your engineers steps into the Lead AI Engineer seat while I shadow them. Everything still in my head — decisions, rationale, the playbook — moves into a written runbook your team owns after I'm gone.
Exit, and after
Day after, indefinitely
I'm gone. Your team is making the calls without me — that was always the point. If something breaks six months later, the first call back is on me. No retainer, no lock-in.
Methodology
Four phases, with the exit built in.
Assess
Week one, I listen — to your engineers, to your code, to your business goals. By Friday, you have a written assessment: what's working, what's at risk, what we do first.
Lead
Then I take the Lead AI Engineer seat. Architecture choices get made. Standards get written. The team has a direction — and someone accountable for it.
Enable
While I lead, I'm teaching. Code reviews, 1:1s, and the production discipline that turns demos into systems your customers can rely on.
Exit
When your team is making the calls without me, I leave. Not a surprise, not a renegotiation — the exit was on the calendar from day one.
Stack
I help teams pick the right tools.
The AI tooling ecosystem changes every month. Most teams chase the new thing. I help yours choose the tools that fit your actual problem, ship with them in production, and walk away from the ones that don't earn their keep.
- LLMs & agents
- LangChain, LangGraph, OpenAI, Anthropic, HuggingFace
- LLMOps
- LangSmith, LangFuse, LangWatch
- ML / training
- PyTorch, Transformers, Fine-tuning toolchains
- Infra & MLOps
- Kubernetes, Docker, Airflow, GitHub Actions
- Cloud
- AWS, GCP, Azure, SageMaker, Vertex AI
About
Fourteen years in software. Eight in AI.
I spent fourteen years writing software — the last eight on AI. Most recently I was CTO of an enterprise AI startup, which is to say I've sat on both sides of this engagement. I've been the founder who needed AI leadership. I've been the Lead AI Engineer who came in. MSc in Data Science, Sapienza University of Rome.
Today I work fractionally — short, deep engagements where the point isn't to stay forever, it's to leave your team better than I found it. I also run llmsengineering.com, where I take on hands-on RAG and agent builds for teams that need delivery rather than leadership.
Based in Rome. Three to six month engagements. Remote, with teams worldwide.
Contact
Ready to talk?
Tell me about your team — what's working, what isn't, what you're trying to ship. I read every inquiry myself and reply within 48 hours. Next steps if we're a fit, an honest no if we aren't.