Senior Software Engineer
Summary
Lead the design and delivery of scalable web services and APIs, mentoring engineers while driving technical plans and engineering culture. This hands-on hybrid role involves microservices, relational and NoSQL databases, and cloud infrastructure.
We are looking for a Senior Software Engineer to join Defaqto and take a lead role in designing, building, and evolving our online systems and services — while helping us push forward one of the most exciting shifts in modern engineering: AI-assisted development across the entire software lifecycle.
Our mission is to help everyone in the UK make better financial decisions. As a Senior Software Engineer, you'll build the products and services that make that possible, working closely with the product team to turn ideas and rapid prototypes into well-considered technical plans, then driving your team to deliver and iterate at pace.
Our Defaqto approach
AI is already central to how we work. We've been actively adapting our AI toolkit and today combine Cursor, Codex, Claude and Copilot in our day-to-day engineering. Crucially, we've moved beyond using AI just to write code — we apply it across the whole SDLC, from discovery and specification through design, testing, documentation and delivery. We're increasingly working spec-driven: capturing intent as clear, structured specifications that our AI tools help us implement, validate and evolve. We also build AI-powered solutions directly into the products our customers use.
This is a hands-on role with real influence, and we're looking for engineers who are genuinely excited to help embed these practices in a real financial services environment.
Our mission is to help everyone in the UK make better financial decisions. As a Senior Software Engineer, you'll build the products and services that make that possible, working closely with the product team to turn ideas and rapid prototypes into well-considered technical plans, then driving your team to deliver and iterate at pace.
Our Defaqto approach
AI is already central to how we work. We've been actively adapting our AI toolkit and today combine Cursor, Codex, Claude and Copilot in our day-to-day engineering. Crucially, we've moved beyond using AI just to write code — we apply it across the whole SDLC, from discovery and specification through design, testing, documentation and delivery. We're increasingly working spec-driven: capturing intent as clear, structured specifications that our AI tools help us implement, validate and evolve. We also build AI-powered solutions directly into the products our customers use.
This is a hands-on role with real influence, and we're looking for engineers who are genuinely excited to help embed these practices in a real financial services environment.
- Design, build, and maintain highly scalable web services, APIs, and backend systems that handle real-world production load with reliability and performance.
- Champion and mature AI-assisted development across the full SDLC — from specification and design through coding, testing, documentation and release — helping the team get more value from tools such as Cursor, Codex, Claude and Copilot.
- Drive our adoption of spec-driven development, turning product intent into clear, structured specifications that guide both people and AI tooling toward correct, high-quality implementations.
- Contribute to the AI-powered features we build into our products for customers, ensuring they are robust, responsible, and genuinely useful in a financial services context.
- Collaborate directly with the product team to evaluate ideas and rapid prototypes, proposing clear technical plans that balance ambition with pragmatism.
- Lead and drive the engineering team through delivery, from sprint planning and technical design through to deployment and post-release iteration.
- Architect and review solutions across the full stack, ensuring consistency in patterns, quality, and long-term maintainability.
- Define and uphold engineering standards including code review, testing strategy, CI/CD pipelines, and observability practices — and evolve those standards for an AI-augmented workflow.
- Partner with product on rapid iteration cycles, keeping feedback loops short, reducing time-to-learn, and enabling the team to move with confidence.
- Proactively identify and address technical debt, performance bottlenecks, and reliability risks before they become problems.
- Contribute to architectural decisions and be a meaningful voice in engineering-wide discussions around direction, tooling, and process.
- Act as an escalation point for complex technical problems, providing clear thinking and solutions under pressure.
- Champion a culture of psychological safety, continuous learning, and high engineering craft within the team.
Essential requirements:
- Significant hands-on experience building and operating highly scalable online systems and services in production environments, consistent with a senior level of ownership and technical leadership.
- Practical experience using AI-assisted development tools (e.g. Cursor, Codex, Claude, Zed, Copilot or similar) as part of your everyday workflow, with a clear view of where they add value and where human judgement remains essential.
- An understanding of, or genuine enthusiasm for, applying AI across the whole SDLC — not just code generation, but specification, design, testing, documentation and delivery — and a desire to help others adopt these practices.
- Strong proficiency in designing and building RESTful/gRPC APIs and microservices architectures, with a deep understanding of trade-offs in distributed systems.
- Solid experience with multiple data storage paradigms: relational databases (e.g. PostgreSQL, MySQL), NoSQL (e.g. MongoDB, DynamoDB, Redis), and the patterns that make each appropriate in context.
- Proven ability to coach and mentor junior and mid-level engineers through code reviews, pair programming, technical guidance, and constructive feedback.
- Experience translating ambiguous product ideas or early prototypes into structured technical proposals and delivery plans — spec-driven thinking is a strong advantage.
- Demonstrated ability to lead an engineering team through a full delivery cycle, from technical design to release, while maintaining momentum and quality.
- Strong understanding of software engineering fundamentals: algorithms, data structures, system design, testing, and operational concerns (monitoring, alerting, incident response).
- Experience working in an agile, fast-paced product environment with short iteration cycles and close collaboration between engineering and product teams.
- Excellent communication skills — able to articulate complex technical concepts clearly to both technical and non-technical stakeholders.
- A track record of pragmatic, outcome-focused decision-making: balancing technical rigour with the need to ship and learn quickly.
Desirable requirements:
- Experience building AI-powered product features (e.g. integrating LLMs, prompt engineering, retrieval-augmented generation, or evaluating and monitoring AI outputs in production).
- Experience defining team practices, guardrails or governance around responsible AI use in engineering.
- Experience designing and consuming gRPC services, including protocol buffer schema design and inter-service communication patterns.
- Familiarity with event-driven architectures and messaging systems (e.g. Kafka, RabbitMQ, SQS/SNS).
- Experience with cloud-native infrastructure and deployment patterns (AWS, GCP, or Azure) including serverless, containerisation (Docker/Kubernetes), and infrastructure-as-code.
- Exposure to stream processing or real-time data pipelines at scale.
- Experience with search technologies such as Elasticsearch or OpenSearch.
- Prior experience in a tech lead or staff engineer capacity, with involvement in cross-team technical decision making.
- Contribution to open-source projects, engineering blog posts, or technical community involvement.
- Familiarity with product analytics, feature flagging, and experimentation frameworks to support rapid iteration.
- Experience with security-by-design principles and implementing secure coding practices across distributed systems.
Your approach to work:
The role is as much about how you work as what you build. We are looking for someone who:
The role is as much about how you work as what you build. We are looking for someone who:
- Takes ownership without being territorial — you share knowledge freely, help others grow, and care about the success of the whole team, not just your own work.
- Brings clarity to ambiguity — you are comfortable working from a rough idea or prototype and can structure thinking around it, increasingly by capturing it as a clear specification.
- Embraces new ways of working — you're excited by AI-assisted and spec-driven development and want to help shape how a financial services engineering team adopts them well.
- Balances speed and quality deliberately — you understand when to move fast and when to slow down, and can make that call with sound reasoning.
- Communicates proactively — you surface blockers early, share progress openly, and keep both your engineering team and product stakeholders informed without being prompted.
Location:
We have offices in various UK locations and you will be expected to attend one of the offices at least 3 days per week:
- Farringdon, London
- Cwmbran, Wales
- Haddenham, Buckinghamshire
Right to Work:
Applicants must already hold a legal right to work in the UK without time restrictions and without the need for future sponsorship. We are unable to provide Skilled Worker visa sponsorship.