Principal Software Engineer
Summary
Most senior hands-on engineer at Defaqto (Fintel), owning engineering standards and leading the shift from AI-assisted to AI-led delivery, plus direct ownership of the highest-risk initiatives such as developer- and AI-agent-facing APIs and MCP servers. Core stack: .NET/C#, TypeScript on Azure, Python, PHP and SQL.
- Own the trajectory from engineers using assistants to write code, to engineers directing agents that write it - with humans firmly in the loop as architect, reviewer and accountable owner.
- Define what good looks like at each step: prompt and context engineering, agent-readable codebases (clear structure, strong typing, rich tests, machine-readable specs), and tooling that makes agent output reproducible, not lucky.
- Make review the new craft - tests as the contract, static analysis and security scanning built into the loop, and no unreviewed AI-authored change reaching production.
- Shift practices towards specification over syntax, so engineers focus on problem framing, acceptance criteria and verification rather than implementation keystrokes.
- Run structured experiments with new models and workflows, measuring lead time, change failure rate and developer experience - retiring anything that doesn't earn its place.
- Set the guardrails that make this safe in a regulated business: secure, licence-aware tooling, provenance and auditability for generated code, and a named human accountable for everything that ships.
- Coach engineers through the shift from writing code to engineering outcomes, bringing sceptics along with enthusiasts.
Turn developer practices into engineering practices
- Build engineering discipline that holds at organisational scale and at the volume agentic delivery produces.
- Codify practice into the paved road - templates, pipelines, linters, policy-as-code and agent instructions - so the right thing is the easy thing.
- Define and evolve engineering standards across Defaqto Technology: code review, testing, observability, security by design and definition of done.
- Hold the line on quality through coaching and pairing rather than policing, and help raise the hiring bar to match.
Take hands-on ownership of what matters most
- Own the highest-risk, highest-upside initiatives end to end - architecture, build, launch and operational reality. What that is will change; the level you operate at won't.
- Design platforms and integration surfaces for both human developers and AI agents: machine-readable capability discovery, unambiguous tool definitions, MCP servers, predictable errors and sensible rate limiting under agentic access patterns.
- Build data governance into the technology itself - entitlements, licensing, lineage and provenance enforced at the point of access, with full audit of who or what accessed data, and when.
- Make quality and trust observable through data contracts and clear freshness signals, so no consumer can silently misread a rating or field.
- Own the consumption experience end to end - onboarding, SDKs, documentation, versioning - treating time to first successful call as a metric you own.
Partner with Product
- Pressure-test feasibility, cost and risk on product ideas early, before commitments are made.
- Surface technology-led opportunities Product hadn't thought to ask for.
- Translate between commercial intent and technical reality in both directions.
Guide squads and evolve the tech stack
- Guide teams towards sound, well-supported technology choices over novelty for its own sake.
- Own continuous improvement of the stack, with every material change carrying a stated benefit and migration plan.
- Lead cross-team architecture decisions, document them as ADRs, and keep our technical debt position honest.
Be a strategic and tactical sounding board
- Act as trusted counsel to the Head of Engineering, CTO and leadership on both strategy and this week's trade-offs.
- Represent engineering reality in commercial, regulatory and roadmap conversations.
- Stay hands-on, building and reviewing the work that matters most.
- Substantial commercial software engineering experience, including time at staff/principal level, with technical influence beyond your own team.
- Deep, current, hands-on ability in a modern stack, with breadth beyond your strongest language. Our core stack: .NET/C# and TypeScript on Azure, Python, PHP, SQL and modern data tooling.
- Real, evidenced experience leading agentic and AI-assisted development in a production engineering organisation - not just personal assistant use. You can show how you changed a team's practices and kept quality intact while doing so.
- A clear point of view on what makes AI-led delivery work: specification engineering, test-first contracts, agent-readable codebases, and review as a first-class discipline.
- Demonstrable ownership of engineering standards across multiple teams - written, embedded in tooling, and proven to change behaviour.
- Strong API and integration engineering, with real care for the experience of consumers - human and increasingly agentic.
- Treats data governance as an engineering problem, enforced in the technology rather than a policy document.
- Sound distributed systems and cloud architecture judgement - resilience, observability, performance and cost, not just diagrams.
- Excellent influencing and communication skills across product, commercial and executive audiences.
- Commercial instinct - you tie technical work to outcomes the business can measure.
- A mentoring track record: senior engineers have visibly grown through working with you.
- Comfort with a moving remit - motivated by the hardest problem right now, not by owning one system indefinitely.
Desirable requirements:
- Experience building or operating agent-facing integration surfaces - MCP servers, tool-calling interfaces or similar.
- Financial services, fintech or regulated data experience, comfortable treating FCA and UK GDPR/ICO expectations as design constraints.
- Experience with data products, BI or analytics platforms — modelling, contracts, quality and lineage.
- Experience of a developer portal, API marketplace or platform-as-a-product.
- Platform engineering and DX work: CI/CD, internal developer platforms, golden paths, self-service tooling.
- Event-driven architecture and legacy modernisation experience.
- Contribution to the wider engineering community - open source, writing, speaking or standards work.
Your approach to work:
Pragmatic - you optimise for outcomes and maintainability over elegance or novelty.