Johan Steenkamp
Summary
I help businesses build AI systems grounded in their own expertise — not generic models that could belong to any company in their industry.
With over a decade of building production systems across fraud detection, industrial monitoring, scientific computing, and geospatial intelligence, I've seen the same pattern everywhere: the most valuable intelligence in a business lives in people's heads, informal processes, and institutional memory. Most AI has no access to any of it.
Orbital is my practice. I work with businesses to surface and structure their operational intelligence, then build AI systems that draw on it. The result is AI that reflects your team's judgment and standards — not generic tools your competitors can license off the shelf.
Principles
Start from the business, not the technology. Every engagement begins by understanding what your organisation actually knows. The technology follows the problem, not the other way around.
Amplify people, don't replace them. The goal is to make your best people's judgment, patterns, and instincts available everywhere they're needed — not to automate the people who developed them.
Build to last, not to depend. Systems should keep working and improving after the engagement ends. Your team should be able to maintain and extend the intelligence base themselves.
Ship products first, build infrastructure later. I focus on solving specific problems with working code, not building elaborate frameworks or perfect architectures.
One person who ships beats a coordinated team. You get me, not a team of juniors. The builder archetype matters more than ever — own the full stack from problem to solution.
How I Work
I work in three phases — Map, Architect, Build — starting from your operational intelligence and shaping AI systems around it.
Map: Surface the judgment, decision patterns, and institutional intelligence inside the business that haven't been made systematic. Identify where AI has genuine leverage versus where it would just add complexity.
Architect: Design the intelligence architecture — a structured representation of how your business actually works — and shape the AI systems around it. Strategy before technology, always.
Build: Deliver durable systems your team can maintain and extend. The value grows over time rather than creating a dependency.
Technical Depth
When it's time to build, I bring deep expertise in the systems that make operational intelligence usable:
- React applications and data visualization — Interactive network graphs, geospatial intelligence, real-time dashboards, and domain-specific tools built with React, TypeScript, AntV/G6, Mapbox, and Deck.gl
- Production AI systems — LLM orchestration, MCP servers, evaluation frameworks, prompt management, and human-in-the-loop patterns using AI SDK, Next.js, and modern AI tooling
- Intelligence architecture — Structuring operational intelligence so it's accessible to both people and AI, including document intelligence, retrieval systems, and decision-support pipelines
- Geospatial data fusion — Multi-source intelligence overlays, temporal-spatial analysis, and interactive map interfaces for complex real-world systems
Experience
AI Systems Engineer
Orbital | Self-employed Apr 2025 – Present
Building AI systems grounded in business expertise — from mapping operational intelligence through to production deployment. Specializing in approaches where AI reflects how businesses actually work, not generic patterns. React applications, AI systems, MCP servers, and geospatial intelligence.
Principal Frontend Engineer
Darwinium | Full-time Sep 2022 – Apr 2025
Led development of the fraud detection frontend — UI, dashboards, and data visualization for a platform that processes billions of digital interactions. Shaped engineering practices for modern React development. TypeScript, React, GraphQL, AntD, AntV, Mapbox.
Digital Architect & Head of Software
Syft Technologies | Full-time May 2018 – Sep 2022
Responsible for end-to-end digital infrastructure and strategy for a scientific instruments company. Led and grew engineering teams. Architected platform systems on AWS. Active developer in full-stack applications using React, GraphQL, and Next.js.
Principal Engineer
Wynyard, Cognevo, & Telstra | Full-time Aug 2014 – Apr 2018
Principal Engineer and Application Architect across multiple technology companies, focusing on data visualization frontends for security products. Led adoption of GraphQL and modern React patterns. Node.js, React, Redux, GraphQL.
Skills
- Frontend: React, Next.js, TypeScript, Tailwind CSS, shadcn/ui, GraphQL, Mapbox, Deck.gl, AntD, AntV (G2, G6)
- Geospatial: Multi-source data fusion, temporal-spatial analysis, network graph overlays, interactive map intelligence
- Backend: Node.js, AWS, DynamoDB, S3, Postgres, SQLite, Supabase (database, auth, storage), Clerk
- AI: AI SDK, LLM APIs, Model Context Protocol (MCP), Prompt/Context Engineering, Intelligence Architecture, Evaluation Frameworks
Education
BSc Eng (Electronics) University of Cape Town
Example Projects
Examples of AI systems and applications I've built:
- Routebook: Cinematic satellite visualization and fitness tracking for Rouvy cyclists, with fly-along route animation, performance overlays, POI creation, and automatic performance metrics
- Deep Search: Production-grade search app with evals, observability, and prompt management
- Darwinium Frontend: Fraud detection UI with interactive dashboards and network graphs
- Syft Instrument Health: Mass Spectrometry instrument performance monitoring
- Mersen R-TOOLS MAXX: Heat sink design and thermal simulation tool