Principal Engineer

Create Future is a digital consultancy that builds digital products and services for major organisations across a wide spectrum of industries. We pride ourselves on a people‑first culture and strong client partnerships.

The bar has moved. Five years ago a strong engineer was measured by what they could build and how well they could mentor others to build it. Today, with Claude Code and agents, we produce quality work at a speed that would have looked superhuman in 2022.
We expect you to own the complete package: architecture, deep engineering foundations, communication, system thinking, and the judgement to direct both your own intelligence and AI toward outcomes that matter.

• Outcome obsessed – you care whether the problem was actually solved, not merely that a clever solution exists.
• Intellectually honest about uncertainty, taking a trust‑but‑verify approach and assuming the surprising bug is the one that will burn.
• Deeply pragmatic – you hold opinions loosely and decide for the systems in front of you, not for a preferred platform or language.
• Bias toward delivery – you iterate from the smallest working piece and treat documents and meetings as a means to that end.
• Relentlessly curious beyond immediate needs – you want to understand how the database stores things or why an inference call costs what it does.

For a Principal to be truly exceptional, AI fluency is a first‑class competency, not a side skill. In practice that means:

• Setting AI up to succeed – you treat context engineering as a craft, architect clean interfaces, and build knowledge bases that enable AI to work on the codebase.
• Reviewing and choosing well – you read far more code than you write, catching assumptions, security flaws, architectural drift, and knowing where models fail.
• Working with non‑determinism – you build with AI components but treat success as a spectrum, using evals, golden datasets, structured outputs and fallback paths alongside unit tests.

• Backend – instinct for distributed systems, eventual consistency, queue health, aging APIs, thoughtful data modelling, and language‑agnostic solutions via AI.
• Cloud – cost‑aware and security‑aware by default, reaching for IaC and composing primitives rather than piecing together managed services.
• Data – modern pipelines, governance, lineage, vector stores and embeddings, treating data quality as seriously as production code.
• Web and mobile – clear view of what to pick today, and the ability to build “good enough” front‑ends yourself, enhanced with AI.

You recognise that technology is only about 30% of the picture; the rest is design, argument, commercial and political acumen, and the clarity to frame outcomes for senior leadership.

• You avoid gold‑plating and name when a project's real problem is not technical.
• You understand the durability of solutions versus fleeting trends, and you decide to keep or remove stack components accordingly.
• You remove unnecessary complexity while strengthening the remaining stack.

• Communicate clearly and frequently – documents, decisions, post‑mortems, design notes that become machine‑readable context for AI.
• Own decisions – you make and own them, preach benevolent dictation when appropriate.
• Mentor in AI fluency – coaching tooling, prompting and review discipline to double team productivity.
• Handle minimal line management – you self‑resolve, raise only by exception, and can manage financial controls when required.
• Disagree well – you argue with evidence and alter your stance when proven wrong.

• The gifted engineer who works in isolation rather than in a team.
• The one fluent with AI but shipping without guardrails and quality gates expected by enterprise clients.
• The one with strong technical opinions that cannot justify them commercially and becomes defensive.
• The pure manager who favours coordination over direct engineering involvement.
• The engineer who will not fully immerse in a client environment – on‑site work and trusted relationships are required.