Technical Competencies
These are new to our capability register — and they're the practice area growing fastest. We've built them through real project delivery, not classroom certification. Every competency below is backed by production systems we've shipped.
Six areas of genuine AI depth. Click any card to see full capability breakdown, tools, and what "expert" actually means for us in that area.
Production-grade systems built on top of foundation models — retrieval pipelines, prompt architecture, context management, and the evaluation frameworks that tell you if the system is actually working.
Multi-step, multi-tool AI agents that operate inside real business workflows. We engineer the guardrails, escalation logic, and audit trails that make agents safe to deploy in production — not just impressive in demos.
When prompting isn't enough. We fine-tune open-weight models on proprietary data, adapt foundation models to specialist domains, and run the evaluations that prove the adapted model is actually better — not just different.
The operational layer that keeps models working after launch day. Feature stores, model registries, drift detection, automated retraining — because a model that worked at go-live and fails six months later is worse than not shipping one.
Enterprise AI that passes legal, risk, and compliance scrutiny. We build the explainability layers, bias audits, and governance frameworks that turn AI from a liability question into a documented, auditable, defensible system.
End-to-end engineering of user-facing AI products — chat interfaces, document intelligence tools, AI-augmented workflows. We handle the full stack: UX, AI backend, integration layer, safety layer, and the observability to know if it's working.
The original three — now with AI deeply embedded at every layer. These aren't unchanged from 2019; they've been rebuilt around AI-era data requirements.
Scalable, observable, AI-ready data pipelines. We build the infrastructure that makes every downstream use case — analytics, ML, AI agents — reliable enough to trust.
Classical ML and statistical modelling — with LLMs used to accelerate the research, feature engineering, and evaluation phases. We choose the right model for the problem, not the most impressive one.
Analytics redesigned for the AI era — NL query interfaces, semantic layers, and decision-driven design. We build analytics that changes behaviour, not dashboards that collect login attempts.
The engineering backbone. AI accelerates delivery here — but the craft of building reliable, maintainable systems at enterprise scale is still a human discipline.
Full-stack enterprise application development — with AI co-pilots embedded across the engineering lifecycle. We ship faster without cutting the corners that cause production incidents.
Making systems talk to each other reliably — and making AI capabilities connect to enterprise systems without breaking them. Event-driven, resilient, and always observable.
AI-accelerated test engineering — from unit to E2E, plus the AI-specific quality concerns that standard QA frameworks don't cover: LLM output validation, prompt regression, and agent behaviour testing.
Depth rating out of 5. Assessed against real project complexity, not certification status. Certifications shown where held.
| Competency | Depth | AI Layer | Certifications / Standards | Years Active |
|---|---|---|---|---|
| ─── AI & Machine Learning | ||||
| LLM Engineering & RAG | Core practice | — | 3 yrs | |
| AI Agent Development | Core practice | — | 2 yrs | |
| Fine-tuning & Model Adaptation | Core practice | — | 2 yrs | |
| MLOps & AI Platform | Core practice | AWS ML Specialty | 4 yrs | |
| Responsible AI & Governance | Core practice | ISO 42001 | 2 yrs | |
| Generative AI Product Dev | Core practice | — | 2 yrs | |
| ─── Data Practice | ||||
| Data Engineering & Pipelines | AI-enhanced | Databricks Associatedbt Certified | 8 yrs | |
| Data Science & ML | AI-enhanced | GCP Professional DS | 7 yrs | |
| Analytics & BI | AI-enhanced | Tableau Desktop Cert | 9 yrs | |
| ─── Engineering Practice | ||||
| Application Development | AI-assisted | AWS Solutions Arch. | 10 yrs | |
| Integration Services | AI-enhanced | MuleSoft Developer | 8 yrs | |
| Test & Quality Assurance | AI-accelerated | ISTQB Advanced | 9 yrs | |
■ Primary — used on most projects ■ Secondary — used where appropriate ■ Available — certified but specialist
Every competency listed is used on live projects, not just in certifications. Our own delivery process runs on the same AI tools we recommend to clients. We know where they break because we've experienced it.
If a capability is out of scope for us, we tell you — and recommend someone who can. We won't staff a project with people who are learning the stack on your budget. Depth ratings are honest, not aspirational.
The AI practice is the fastest-moving space in engineering. We run internal model evaluations monthly, rotate primary tools as capabilities shift, and train the team continuously. The competency register is reviewed quarterly.
Tell us the problem you're trying to solve. We'll map it to the right combination of competencies — and be straight with you about where we can genuinely add value and where you should look elsewhere.