Sobre esta vaga de Lead Software Engineer - Solution & Data Architecture - B2B SaaS Fintech na Landytech
Landytech is building the intelligent operating platform for modern investment management. Our AI-powered platform, Sesame, brings together investment, corporate and accounting data across asset classes, custodians, currencies and legal entities, creating one secure, trusted source of truth from which our clients can understand their wealth and act with confidence.
Sesame is much more than a reporting tool. We build technology that helps asset owners, asset managers, private banks and trust and company service providers run their entire investment ecosystem: automating complex data and document ingestion, surfacing portfolio and risk insights, anticipating liquidity needs, supporting investment decisions and deal flow, streamlining collaboration and turning intelligence into action through AI.
From family offices managing multigenerational wealth to financial institutions serving clients at scale, Sesame replaces fragmented data and manual processes with clarity, control and smarter decisions.
Why this role exists
Our domain is a healthy challenge: multi-custodian, multi-currency, multi-entity financial data, modelled thoughtfully and available at scale. The platform is Kotlin and Spring microservices, with Python where it pays off: metrics, analytics and our AI work. Good features start well before any code gets written, with clear communication about the outcomes to be delivered, followed by planning, prototyping when it helps, and a design the team agrees on.
As technical lead of an R&D team, you'll work closely with a Product Manager on initiatives, improvements and bugs: shaping the work, breaking it down, handing it out across the team, and owning what ships.
You go deep enough into the requirement to push back on it, ask the questions that need asking, and tell apart what the client needs from what the requirement says.
Then you work out how it fits. Usually the right answer is the simple one built on architecture we already have, and defending that is part of the job. Sometimes it isn't, and you're the one who flags that this is a truly new capability, writes the spec and plan, and takes it to our other architects to poke holes in before we commit.
You'll do all this in a team that uses coding agents every day, and you'll help shape how we do that well.
What you'll own
You own the partnership with Product: one PM, one lead engineer, one roadmap. You sit with product and domain experts before the ticket exists, understand the business problem, push back on the requirement where it needs it, and come back with honest trade-offs on cost, risk and time. You plan, size and hand out the work, and keep the team unblocked while it ships.
Security, scalability, availability and performance are design inputs on every initiative, not a hardening phase at the end. You cover tenant isolation, auth, data protection and auditability, because our clients' data is about as sensitive as it gets. You know how the system behaves under load and at month-end when everyone runs reports at once, you set the SLOs, and you make sure we can see whether we're meeting them. You are the escalation point when the team hits something genuinely hard, and you go in and solve it with them.
For every significant initiative you produce the design: what changes, in which services, what the contracts and data flows look like, what we reuse and what we leave alone. You write it down, take the challenge from our other architects, and improve it. When a requirement exposes a gap in the platform, you name it and propose what should exist.
You own feature architecture end to end, from the React frontend through our Kotlin and Spring services, across data stores and events, down to Azure. You decide what goes where, and push hard for the simplest solution the existing architecture can carry.
You set the coding standards, API design, testing, quality gates, and security and dependency hygiene. That now covers how we work with coding agents: the rules they follow, the skills and MCP integrations we build over our own systems, and the review process that holds quality as more code gets generated. You're the one who challenges what an agent proposed, because plausible code that passes its tests can still be wrong about concurrency, a data model or a failure mode.
You model the financial domain: positions, transactions, instruments, valuations, entities and hierarchies, so it holds up as new asset classes, custodians and jurisdictions arrive. You build pipelines that stay correct when the source data is messy, late or wrong, and fast enough to run over long histories on demand.
You line-manage a squad: objectives, one-to-ones, feedback that moves careers, hiring, onboarding and code reviews people learn from. You bring back what's new and make sure it lands with the team rather than staying in your head.
You stay hands-on throughout — this is not a role where you stop writing code.
What we're looking for
- 8+ 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.
- Experience leading engineers. You've line-managed or formally led a team, and you can point to people who got significantly better while working for you.
- 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.
Our stack
- Core backend: Kotlin, Java 17+, Spring Boot & Co, JPA/Hibernate, SQL and NoSQL, Elasticsearch, Gradle, JUnit/AssertJ/MockK
- Metrics, analytics and AI: Python, FastAPI, Polars, LangChain
- Frontend: React (TanStack Query/React Router/react-hook-form + Zod), TypeScript, nx.dev, Tailwind CSS/shadcn/ui, Vitest/Playwright/MSW, Vite, Recharts
- Platform: Azure, Azure DevOps (CI/CD), Kubernetes, Docker, cloud storage, messaging and events, Git, SonarQube
- AI in our workflow: Claude Code and Codex day to day, custom skills, MCP servers over our own platform, LLM-powered document and data ingestion
What the first year looks like
- Month 1: you know the platform, the domain and the team, and you've shipped something real.
- Month 3: you and your PM are running your initiatives together, and you've written the spec for a significant cross-service feature.
- Month 6: your fingerprints are on our engineering conventions and on how the team plans, designs and reviews work.
- Month 12: your team is noticeably stronger than the day you arrived, and the decisions you made are holding up under load.
Why join now
You're joining early enough to shape the platform and late enough that it has real clients, real scale and real revenue behind it. The problems are hard, the domain is deep, and the industry is genuinely ready for what we're building. You'll work with an international team across London, Paris, Pune and beyond, and you'll have a real voice in what we build.
Our Benefits
- An opportunity to work in a fast growing fintech revolutionizing investment reporting
- Hybrid style of work/WFH allowed depending on role
- Competitive salary & stock options package
- Private medical insurance for you and your family members
- Pension Plan with NEST
- Cycle to Work Scheme and gym allowance
- Office food & drinks, regular socials
If this sounds like a match to you, we are looking for to receiving your application!