Software Development Engineer in Test; SDET

Retire the ERP.

Light exists to replace factory-era ERPs with software that feels alive. Our Smart Financial Platform gives modern, global companies superpowers—automated accounting, real-time reporting, and financial flows that move at the speed of the business.

We build with our customers, ship fast, and obsess over craft. In a short time, Light has gone from idea to the operating core for leading companies like Lovable, Legora, and Keyshot. People don’t just use Light—they enjoy it.

We’re an early team defining a new software category. Think engineers who love debits and credits, designers who care about reconciliation states, and operators who treat finance as a product. If you’re excited to modernize how the world runs money—one workflow at a time—you’re in the right place.

Backed by world-class investors and advised by industry titans, we’re building category-defining products with the freedom to ship ambitiously and own outcomes.

Come help us make Light the global default for next-gen finance.

At Light, we are building the Global Financial Platform. To achieve this ambition, we are scaling our engineering organisation rapidly. That growth only works if we get quality right.

You will join the Foundation Team, the force multiplier for our entire engineering organisation. Our mandate is to "build the factory that builds the product." As an SDET, you will not just be writing tests for a feature team — you will be architecting the internal quality infrastructure that enables every engineer at Light to ship with confidence.

We are looking for someone who is obsessed with test engineering as a discipline but grounded in the reality of production systems. You will help us move beyond ad-hoc testing to build robust frameworks, define our internal standards for quality, and ensure our teams can ship multiple times per day, safely and with confidence.

• Build the Infrastructure: Design and implement test frameworks, fixtures, and data management patterns that make good testing the path of least resistance across multiple languages and frameworks. Immediate focus is Type Script, Kotlin, Python, and Terraform.

• Solve Test Data: Build strategies for realistic, safe test data in a fintech context — synthetic data generation, anonymisation, and environment management that lets engineers test confidently without touching production data.

• Define the Standard: Create the "paved road" for product engineers — standardising how every team at Light writes, runs, and maintains tests. Own the testing section of our engineering playbook.

• Solve for Trust: Build quality gates in CI/CD that catch problems before production. Implement test observability so failures are obvious and actionable, not cryptic and ignored.

• Bridge the Gap: Write tests in high-risk areas where coverage is critical — not as permanent ownership, but to model good practice, stabilise production, and demonstrate what good looks like.

• Scale the Culture: Coach engineers across all teams on test design and help them adopt new practices. Your success is measured by how quickly quality ownership distributes to delivery teams.

• Test the Non-Deterministic: Build evaluation frameworks for AI features — prompt regression testing, golden datasets, and reliability metrics that let us deploy AI with the same confidence as traditional code.

• Test Engineering Background: You have significant experience building test infrastructure and tooling, not just writing tests. You understand the difference between unit, integration, and E2E testing — and when each matters.

• Polyglot Capabilities: You are comfortable working across multiple languages. Our stack includes Kotlin, Type Script, and Python. Mastery of all three is not required, but resistance to learning is a deal breaker.

• Platform Mindset: You get more satisfaction from unblocking 10 engineers with a great tool than from shipping a single feature yourself. You think in systems, not tasks.

• Focus on Reliability: You hate flaky tests. You understand that trust is the biggest bottleneck to test adoption, and you know how to build the observability and diagnostics necessary to generate…