Engineering generalist: system architecture, product-system design, delivery, infrastructure troubleshooting, documentation, and team communication - with a preference for controlled, reversible automation.
Impact areas
Strategic clarity
Make architecture, dependencies, constraints, ownership, and workflows legible for better investment and delivery decisions.
Root-cause diagnosis
Pinpoint failures under production pressure - from logs and routing through to the owning component and fix path.
Context switching
Move between domains, codebases, and time zones without cross-contamination - explicit boundaries and durable handoffs.
Dependable delivery
Connect diagnosis, narrow change, verification, and systemic learning so recovery strengthens the operating model.
Scalable platforms
Create direction, scaffolds, standards, and contribution paths so domain experts can own and extend systems.
Governed AI
Design AI workflows that increase judgment and execution speed while preserving evidence, boundaries, and human accountability.
Systems & infrastructure
Development
Engineering practice
- Docs-as-code - Markdown, MkDocs Material, GitHub Pages
- API contracts - design, endpoint validation, OpenAPI
- Controlled delivery - narrow branches, explicit promotion, runtime verification
- Cross-layer production diagnosis (logs, nginx, PM2, environment routing)
- Data migration planning and execution
- Web scraping, crawling, and integration APIs
- Legacy system maintenance, modernization, and performance tuning
- Visual system mapping and architecture synthesis
- Automated browser testing and UX verification
AI & automation
- Local-first LLM workflows (LM Studio, MLX)
- Checkpointed background workers and resumable pipelines
- Deterministic preprocessing and bounded model output
- Cursor-assisted development and agent orchestration design
- Privacy-tier design - employee filtering, collection boundaries, immutable sources
- Structured Markdown knowledge stores and Tier-1/Tier-2 synthesis
- Semantic event preprocessing and task-fit model routing
Leadership & management
- Engineering manager / lead - teams to ~15 engineers; delivery, stakeholder and shareholder reporting
- Solution architecture - system design, integration boundaries, platform direction across services and repos
- Global programme delivery - discovery through production, on-site and remote
- Technical direction across services, repositories, and environments
- Mentoring through context - scaffolds that enable ownership
- Executive translation of architecture, incidents, and trade-offs
- Operational credibility - close enough to code and production to verify standards
- Recruitment process design and team coordination