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# Senior Software Engineer - Solution & Data Architecture - B2B SaaS Fintech

- **Company:** gb
Landy Tech
- **Location:** UK (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Data Analysis, Microsoft Azure, Cloud Computing, Profiling, Continuous Integration, Data Architecture, Extract Transform Load (ETL), Elasticsearch, Fault Tolerance, Gradle, Hibernate (Java), Java Persistence API, Python (Programming Language), Key Management, Load Testing, NoSQL, Standard Sql, SQL Databases, TypeScript, Data Ingestion, Tailwind, ReactJS, Large Language Models, Claude Code, Spring-boot, Scalability Testing, Backend, Git, Fastapi, Kotlin, Event Driven Architecture, Webpack, AI Platforms, Kubernetes, Information Technology, Free and Open-Source Software, Front End Software Development, Docker, Microservices
- **Published:** October 15, 2026
- **Apply:** https://www.totaljobs.com/job/senior-engineer-saas/landy-tech-job108177683

## About the Role

* 5+ years building backend systems in production, with real depth in Kotlin and/or Java (17+) and the Spring ecosystem (Boot, Web, Security, Data).
 * A track record of architecting systems, not just services: you've owned significant design decisions in a distributed or microservices platform and lived with the consequences.
 * Strong data modelling and SQL skills, plus experience designing data ingestion, transformation or ETL pipelines. You've dealt with data you couldn't trust.
 * Enough Python to design and review it. Our metrics, analytics and AI services are written in it, so you need to be able to reason about them, not to be a Python specialist.
 * Fluency across the boundary: you can read and reason about a React/TypeScript frontend and hold a serious conversation about Kubernetes, cloud networking and cost.
 * You work well with Product. You've partnered closely with a PM, dug into complex business requirements, challenged them, and turned them into plans a team could execute.
 * You write. Technical specs, design docs, ADRs. Clear enough that another architect can challenge them and an engineer can build from them.
 * Comfortable with AI-assisted development. You use coding agents day to day and have a view on where they help and where they quietly cause damage. Experience writing skills, MCP integrations or agent conventions for a team is a strong plus.
 * Security is instinctive for you. Secure-by-design services, authentication and authorisation done properly, tenant and data isolation, secrets and key management, dependency and supply-chain hygiene. You've worked somewhere the data mattered.
 * You've built for scale and kept it up. Designing for growth in users, data volume and history; understanding availability, failure modes, graceful degradation and recovery; and being the person who owns the incident rather than watching it.
 * Performance is something you measure. Profiling and load testing before optimising, query and caching strategy, sensible use of async and batch, and knowing which numbers actually matter to a client waiting on a report.
 * A real testing habit, and a view on what belongs where: unit, component, integration, contract, end-to-end, and performance and scalability testing. You know which of these earns its keep on a given change, and which ones teams quietly skip until it hurts.
 * Comfortable with Docker, Git, trunk-based or short-lived branching, and CI/CD as code.
 * You've led work, if not people. You've been the technical lead on a project or a feature others built on, and you've mentored engineers who got better for it.
 * You lead through influence and clarity. You explain a design to a junior engineer and a product director in the same afternoon, in the right words for each.
 * Fluent English. Degree in Computer Science, Mathematics or another STEM subject, or equivalent experience.

Bonus points

You don't need to come from finance. You do need to be curious about it, because the domain is half the job.

Azure and Kubernetes · event-driven architectures, queues and asynchronous processing · Elasticsearch or NoSQL · observability and SRE practice · security or compliance work in a regulated environment · Python for analytics or LLM applications · financial services or fintech experience · open-source contributions.

Our stack

 * Core backend: Kotlin, Java 17+, Spring Boot & Co, JPA/Hibernate, SQL and NoSQL, Elasticsearch, Gradle,
 * Metrics, analytics and AI: Python, FastAPI, Polars, LangChain
 * Frontend: React, TypeScript, TanStack Query, Tailwind CSS and shadcn/ui, Vite, nx.dev
 * Platform: Azure, Azure DevOps, Kubernetes, Docker, messaging and events, Git
 * AI in our workflow: Claude Code and Codex day to day, custom skills and MCP servers over our own platform