Senior Software Engineer, Quality Engineering

Your Role

As a Senior Software Engineer on the Platform team, you will build and own the frameworks, tooling, and CI/CD infrastructure that let Alpaca’s engineers ship new features quickly and reliably. This is a software engineering role at its core: you will spend most of your time writing Go, designing automated test frameworks, and digging into application code and Kubernetes when needed. Just as importantly, you will help redefine how we use AI to raise the bar on quality - leveraging LLMs and AI-driven tooling to generate tests, catch regressions before they ship, and turn every incident into durable, automated coverage. We are looking for engineers who treat quality as an engineering discipline and see AI as a force multiplier for it - people who build the systems that make testing fast, reliable, and effortless for the teams that depend on them.

Things You Get To Do

Design and build automated test frameworks across our REST and gRPC API surface.

Leverage AI and LLM-based tooling to accelerate test generation, harden regression coverage, and turn production incidents into automated tests - embedding these practices into the frameworks the whole engineering org relies on.

Build and maintain CI/CD pipelines - we use a mix of GitHub Actions and Google Cloud Build.

Design and execute load, stress, and scalability tests to ensure our platform can handle growing demand.

Introduce chaos engineering practices - designing fault-injection and resilience experiments that surface failure modes before our customers do.

Standardize tooling and infrastructure to improve the day-to-day developer experience.

Partner with other teams to raise test coverage, reliability, and speed across services.

Dig into application code to root-cause failures and drive fixes to completion.

Mentor and guide product engineers, fostering a culture of quality and continuous improvement.

Who You Are (Must-Haves)

You have 5+ years of experience as a software engineer building and maintaining production systems.

You have written code in strongly typed languages and have at least 1 year of experience with Go.

You are fluent with AI-assisted engineering - you actively use LLM-based tools in your workflow and have a clear point of view on where they elevate quality (and where they don’t).

You have built and maintained CI pipelines before - ideally with GitHub Actions or Google Cloud Build.

You have designed and built automated test frameworks, and you understand the challenges microservices pose for reliable integration and end-to-end testing.

You are familiar with Kubernetes beyond the basics - you can write a Helm chart for a new service with relative ease, you understand best practices around security, and you have prior job experience or certifications to prove this.

You have worked at a startup before - you understand that things don’t always go according to plan, that there is significant technical debt, that some tasks just need to be done, and that sometimes there are no processes or documentation to guide your hand.

You are not afraid of taking a task from start to finish - gathering requirements, figuring out and implementing the best technical solution, then deploying and monitoring the results.

Who You Might Be (Bonus Points)

You have used AI/LLM tooling to build QA automation - test generation, flaky-test triage, or incident-to-regression pipelines - and can speak to what worked and what didn’t.

You have written code in Python or TypeScript, and can build efficient Dockerfiles and secure container images.

You have implemented load tests with k6 (REST) and ghz (gRPC) and have experience analyzing pprof/trace output.

You have done IaC deployments with Argo CD or Terraform, or have used Google Cloud Platform and Google Kubernetes Engine before. You are familiar with Tilt and have written a Kubernetes Operator before.

You have practiced chaos engineering - running fault-injection or resilience experiments with tools like Chaos Mesh, LitmusChaos, or Gremlin.

You are familiar with testing event-driven systems using Kafka (or even better, Redpanda).