Team
Team
An effective engagement team combines six distinct disciplines. Each role is accountable for a category of risk that the others are not well placed to identify, which is why we staff against all of them rather than assembling a group of generalists.
AI Engineer
Turns a model into an operational service, covering serving infrastructure, inference performance, tool integration and the surrounding software engineering. The emphasis is on systems that run reliably in production rather than on analysis of data.
Data Scientist
Collects and analyses data, applies statistical and machine learning methods to understand and predict, validates models and communicates findings. On our engagements this role also owns evaluation design and the statistical basis for determining whether a change represents a genuine improvement.
Agent Engineer
Prototypes agent architectures, tests them against the client’s actual operating constraints, and develops the approaches that prove viable into a framework that the client’s own team can operate.
MLOps / Platform Engineer
Deployment, CI/CD, registries, monitoring, retraining automation, rollback and incident response. Keeps systems accurate, available and governable after launch.
Data Engineer
Pipelines, data contracts, quality controls and lineage. This is the foundation on which every other discipline listed here depends.
AI Governance Specialist
Risk classification, human-oversight design, documentation and evaluation evidence, mapped to the frameworks a client’s regulator cares about.
How we staff an engagement
QAI Labs operates as a small core group supported by a wider network of specialists. This structure is deliberate: it keeps the people who scoped the work involved in delivering it, and it allows us to decline work for which we are not the appropriate team.
A named engineer owns the work
One person is accountable for delivery from the first conversation to handover. You are not passed to a different team once the contract is signed, and you always know who to call.
The rest of the team is sized to the job
We assign the disciplines that a piece of work genuinely requires rather than staffing to a standard template. A six-week discovery, for example, does not require a platform engineer from the first day.
We work inside your team, not beside it
We work in your repositories, follow your review process and attend your stand-ups. Where a client’s own engineers are not actively working on the code during the build, the handover at the end is unlikely to succeed.
Specialists come in for the parts that need them
For accreditation, sector-specific regulation or unusual hardware we bring in a specialist with direct prior experience, rather than developing that experience at the client’s expense.
We do not publish headcount figures, as total headcount says little about the quality of any individual engagement. What matters is who is actually assigned to your work. Ask us during the first call and we will set out the proposed team in full, including any areas where we would bring in an external specialist.
Find out who would be assigned to your project
Give us an outline of what you are looking to build and we will set out which of these disciplines the work requires, who would lead it, and the points at which we would expect a member of your own team to be working alongside us.