Allan Mwenja Portfolio
Agentic AI Engineer at Kuuka
Nairobi-based AI Engineer whose "Projects" section is five real, shipped products — HireBits AI, PDPBits AI, FreightFit AI, Tatua AI Platform, Resumatch — each with its own live demo AND source code link, not screenshots of hypothetical work.
Location
Nairobi, Kenya
Companies
Skills
Notable
- Shipped 5 production AI products with public live demos and source code (HireBits AI, PDPBits AI, FreightFit AI, Tatua AI Platform, Resumatch)
What makes it work
A breakdown of the choices that make this portfolio stand out.
Every project ships both a live demo and code, not one or the other
HireBits AI, PDPBits AI, FreightFit AI, Tatua, and Resumatch each carry a "Code" link and a "Live Demo" link side by side. Most portfolios force a choice — a polished screenshot with nothing to click, or a GitHub repo with no way to see it running. Doing both for five separate projects removes any doubt that this is real, working software.
A stat strip that quantifies the resume before it's read
"5+ Years of Engineering," "4 Roles Across Startups & Enterprise," "30+ Automation Systems Built" sits directly under the hero, next to a professional headshot. Three numbers do the work that a paragraph of self-description would otherwise have to do, and they're checkable against the work-experience timeline right below.
A coherent career arc, not a disconnected job list
Full Stack Engineer (freelance, 2020–2023) → Software Engineer Intern at Ardagh Group → Automation & Operations Engineer building n8n/Zapier pipelines → Agentic AI Engineer at Kuuka today. Each role visibly builds on the last — automation work naturally led into agent orchestration — so the timeline reads as a deliberate specialization, not a scattered resume.
Named tools instead of buzzwords for an emerging niche
The skills section lists LangChain, LangGraph, MCP, and Claude Code specifically rather than a vague "AI/ML" tag. In a field flooded with generic "AI enthusiast" self-descriptions, naming the exact orchestration frameworks and protocols signals real hands-on production experience.
What AI Engineers can take from this
Specific, actionable tips to apply to your own portfolio — no generic advice.
Pair every project with both a live demo and a source code link — one or the other leaves room for doubt; both removes it.
Put 2-3 checkable numbers (years, roles, systems shipped) in a stat strip right under your hero — it does more work in five seconds than a paragraph of self-description.
Structure your work-experience timeline so each role visibly leads into the next, rather than presenting jobs as an interchangeable list — a coherent arc reads as intentional specialization.
In a hyped or crowded niche, name the specific frameworks and protocols you actually use — specificity is what separates real practitioners from buzzword surfers.
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