Principal Engineer

About the role

We are hiring a Principal Engineer to own the hardest technical problems in our product and see them through from first sketch to stable production. You will set technical direction, design systems that scale, and raise the engineering bar through your own work and the people around you. This is a hands-on leadership role: you write code, review designs, and ship.

What will you do?

You will own outcomes, not just tasks. Expect to spend your time on the following.

• Own projects end to end. Take an ambiguous problem, shape the requirements, design the solution, break down the work, deliver it to production, and stay accountable for how it runs afterwards.

• Lead system design. Author and review architecture for services, data pipelines and integrations, with clear trade-offs on scale, latency, cost, consistency and reliability.

• Write and review critical code. Build the hardest components yourself, and set standards for code quality, testing and maintainability through code and design reviews.

• Own deployment and operations. Design CI/CD, infrastructure and release strategies. Drive observability, on-call readiness, incident response and post-incident learning.

• Solve hard problems. Debug production issues across the stack, and find root causes in performance, concurrency, data and scaling problems.

• Mentor and multiply. Coach senior and junior engineers, grow future tech leads, and make the whole team faster and more confident.

• Partner across functions. Work with product, design, data and business teams to turn goals into technical plans, and to say no or reshape scope when needed.

• Shape technical strategy. Guide build-versus-buy decisions, manage tech debt, evaluate new technologies, and contribute to the engineering roadmap.

• Raise the bar. Help define engineering practices, hiring standards and culture, and take part in interviewing.

What are we looking for?

• Bachelor's degree in Computer Science or a related field, or equivalent practical experience.

Core engineering

• 10+ years of professional software engineering, with a track record of shipping and running production systems.

• Strong computer science fundamentals: data structures, algorithms and complexity, operating systems, networking, databases and concurrency.

• Fluency in at least one major backend language (for example Python, Go, Java, or Node.js/ TypeScript) and the ability to pick up others quickly.

• Deep knowledge of relational and NoSQL data stores: schema design, indexing, transactions, query tuning and replication.

System design and problem solving

• Proven ability to design distributed systems that are scalable, fault tolerant and cost aware, and to explain the trade-offs clearly.

• Experience with APIs, event-driven and asynchronous architectures, queues, caching and service-to-service communication.

• A structured approach to ambiguous problems: break them down, test assumptions, decide with incomplete data, and measure results.

• Strong debugging instincts, including performance profiling and production troubleshooting.

Delivery and operations

• Have led at least two significant projects from inception to production, including planning, milestones, risk management and launch.

• Hands-on experience with deployment: CI/CD pipelines, containers (Docker, Kubernetes), a major cloud (AWS, GCP or Azure), and infrastructure as code.

• Practical experience with monitoring, logging, alerting, SLOs and incident management.

• Habit of writing tests and automation, and of leaving systems more reliable than you found them.

Leadership and communication

• Experience leading engineers without formal authority, through influence, mentoring and clear technical writing.

• Excellent written and verbal communication: design docs, RFCs and concise updates to non-technical stakeholders.

• Ownership mindset, sound judgment on priorities, and comfort working in a fast-moving environment.

Nice to have

• Experience in fintech, lending or another regulated, data-heavy domain.

• Exposure to AI/ML or LLM-based systems in production: model serving, evaluation, retrieval, and cost and latency management.

• Deep experience with data engineering: streaming, batch pipelines, warehouses or search systems.

• Security and compliance awareness: authentication, encryption, audit trails, secure SDLC.

• Experience with multi-tenant SaaS, high-throughput systems or zero downtime migrations.

• Open-source contributions, conference talks, or technical writing.

• Experience scaling an engineering team or helping set up hiring and onboarding practices.

Skills

Python, Java, NodeJS (Node.js), TypeScript, Systems design, Architecture, Distributed Systems, Scalability, Fault tolerance, Performance optimisation, Data Structures, Algorithms, Complexity Analysis, Concurrency, Operating systems, Networking, Databases, SQL, NOSQL Databases, Schema Design, Indexing, Transactions, Query optimization, Replication, Microservices, API design, RESTful APIs, event-driven architecture, Asynchronous processing, Message queues, Caching, Cloud, DevOps, Amazon Web Services (AWS), Google Cloud Platform (GCP), Azure, Docker, Kubernetes, CI/CD, Infrastructure as Code, Reliability, Production Operations, Monitoring, Logging, Alerting, SLOs, Incident management, Root cause analysis, Code quality, Automated testing, technical strategy, Deployment, Production support, Profiling, Latency Optimization, throughput, cost optimization