The engineer behind DBHQ

DBHQ is Daniel Grimes - one principal engineer, 26 years of building software where it had to work.

Daniel Grimes, Director of DBHQ

Daniel Grimes

Director, DBHQ

Who is Daniel Grimes?

Strip away the sectors and the titles and the work is always the same - find what a stuck business actually needs, then build it, usually somewhere getting it wrong is expensive. First engineer on a defence programme. Design authority on a £1B regulated banking platform. Sole architect behind a digital identity infrastructure - across defence, banking, insurance, energy, commodities, healthcare and identity.

For the last year or so I have pointed that same instinct at modern AI. It reads a system faster than I can, drafts at volume, and never gets bored on the fiftieth endpoint. I decide what to ask, what to build and what ships.

How I work

Remote-first from the UK, on-site when it counts. I price on the outcome wherever I can, and on a clear day rate where that fits better - either way you know the cost before we start. No account layer between you and the engineering, no hand-off from the people who sold it to the people who build it, no forty-page decks: a working system and a clean handover.

You can engage DBHQ two ways: to build a specific thing on a fixed price - or to own a delivery that has to reach production, through the release, the operational readiness and the handover. The commercial shape differs; the engineering standard does not.

Recommendations

See my recommendations on LinkedIn

What do I actually do?

Real problems rarely sit in a single discipline. The five I work across:

  • Full-stack engineering

    Architect, software engineer, database engineer and DevOps engineer. One person, the whole stack.

  • Integration and automation

    Connecting the systems that do not talk: CRMs, finance stacks, databases, SaaS estates, legacy applications. The unglamorous work where the value is.

  • Cloud architecture

    Azure end to end: landing zones, networking, security, cost. Platforms from zero, and rescues of platforms that grew without a plan.

  • AI delivery

    Getting AI out of the pilot and into production: LLM platforms, retrieval and recommendation systems, agentic workflows, and the guardrails that make them safe to run.

  • Regulated-grade delivery

    FCA, SOX and defence-grade practices, applied in proportion at commercial pace.

Fifteen minutes will tell you if this fits

Bring the problem - the stalled pilot, the systems that do not talk, the manual process eating your team. You will get a straight answer on whether it is sprint-shaped, roughly what it would cost, and when it could be running.

I reply within 24 hours