Independent AI & engineering leader
AI, made consequential
I lead the engineering organisations that turn ambitious technology into measurable advantage.
01Position
Models do not create advantage.
Operating systems do.
I connect strategy, production AI, organisation design and delivery discipline—so the technology changes a customer or commercial outcome, not just a demo.
Babagana Zannah is an independent AI and engineering leader who turns ambitious technology into measurable customer and commercial outcomes. He connects strategy, production AI, organisation design and delivery discipline across retail, logistics, e-commerce and SaaS. His work spans personalisation, recommender systems, LLMs, distributed platforms and engineering organisations of up to 68 people.
02Operating system
From intent
to impact.
A four-part system for moving AI and engineering work through the organisation without losing commercial intent.
- 01
Frame the consequence
Define the customer behavior, commercial result or operational shift that must change.
- 02
Design the system
Choose the architecture, evaluation loop and guardrails that make the promise production-safe.
- 03
Build the organisation
Create ownership, decision clarity and an environment where strong engineering can compound.
- 04
Prove the outcome
Instrument what matters, learn from reality and reinvest only where the evidence earns it.
03Selected evidence
The work
has receipts.
Selected outcomes across AI, commerce, logistics and engineering effectiveness.
01
AI personalisation · Retail
Built the capability that moved how customers discover.
Production personalisation delivered a +2.7% discovery CTR, +1.8pp conversion and +£11 session value.
02
Engineering effectiveness · Commerce
Increased pace while improving operational control.
Deployment frequency rose from 14 to 52 per day, alongside a lower failure rate and faster recovery.
03
Machine learning · Logistics
Turned pricing intelligence into commercial growth.
ML pricing at DHL / Saloodo contributed an 11% commercial uplift while strengthening the data capability behind it.
04Capabilities
Depth across the whole system.
AI systems
Personalisation, recommenders, experimentation, LLMs, RAG, vector search, model evaluation, safety and privacy.
Organisations
Engineering strategy, organisation design, leadership development, hiring, succession, OKRs and investment cases.
Platforms
Distributed systems, mobile, APIs, data pipelines, cloud architecture, SLOs, observability and incident response.
05Field notes
Thinking,
made useful.
Frameworks for leaders who need AI to survive contact with real organisations.
- AI Experimentation The 48-Hour LaboratoryWhy hackathons can become the missing operating system for AI learning.
- Adoption Respecting the CraftHow to introduce AI without insulting experienced engineers.
- Scale Scaling AI Engineering TeamsCulture, ownership, and the courage to explore without losing production grip.
- Distributed Teams Async Trust & Outcome-First CultureRemote-first operating patterns for AI delivery across time zones.
06Foundations
Education
- MBA Quantic School of Business and Technology, Distinction
- MSc Artificial Intelligence & Machine Learning, University of York, Distinction
- BSc Computer Science, Middlesex University, First Class; Best Computer Science Student
10+ years · teams up to 68
Across retail, logistics, e-commerce and SaaS—combining technical depth with the commercial judgment to know what should be built.
Full profile on LinkedIn07Questions
Useful answers,
without the theatre.
- Who is Babagana Zannah?
- Babagana Zannah is an independent AI and engineering leader based in the United Kingdom and working globally. He turns ambitious technology into measurable customer and commercial outcomes across AI systems, engineering organisations and digital platforms.
- What does Babagana Zannah do?
- He connects strategy, production AI, organisation design and delivery discipline. His work spans personalisation, recommender systems, LLMs, RAG, model evaluation, distributed systems, observability and engineering organisations of up to 68 people.
- What kinds of engagements does Babagana Zannah take?
- He takes select engagements where AI or engineering work needs technical depth, organisation design, delivery discipline and commercial judgement. The current starting point is a direct conversation by email.
- What results has Babagana Zannah delivered?
- Published outcomes include +2.7% discovery CTR, +1.8 percentage points in conversion and +£11 session value from personalisation; deployment frequency increasing from 14 to 52 per day; and an 11% commercial uplift from ML pricing at DHL / Saloodo.
Make it
matter.
Bring me in when the work needs technical depth, organisation design, delivery discipline and commercial judgment.
Start a conversation