Subscript

• Make sure tests consistently run fast and green means green • Maintain staging and test environments that are useful • Help review code with a focus on reliability, edge cases, and failure handling • Build and maintain integration and end-to-end test suites • Close gaps in test coverage by writing tests yourself • Monitor AI workflow correctness and audit individual workflows to catch regressions • Design and maintain eval suites for LLM features • Build a repeatable process for validating prompt changes before they ship • Design and implement monitoring, alerting, and dashboards so we understand system health at a glance • Own observability for our data pipelines external integrations, and AI workflows • Make sure we know about failures before customers tell us

The stack: Node.js/Express, TypeScript, React, Postgres, Clickhouse, MongoDB, Heroku                                                                    The product: We're building agentic software for Finance and Operations teams to automate high-volume workflows across systems—from AP and AR to payroll, inventory, and reconciliations. See www.woodrow.ai                                                                  The way we work:                                                                                                                                - This is a remote job—work anywhere you want, in any timezone on earth (or outside it).                                                        - We are an asynchronous team—no scheduled meetings. We rely on each team member to pick their own schedule and communicate clearly in writing and recorded videos.                                                                                                              - We operate completely autonomously—no one will tell you what to do, we'll tell you the goals and you'll figure out how to work towards them with the rest of the team.                                                                                                                      The role: We're looking for our first Quality & Reliability Engineer who thinks about quality as a system, not a phase at the end of development.  You'll own quality and reliability across the stack—from test infrastructure to production monitoring to LLM evals. This is a founding role: you'll assess what we need, prioritize ruthlessly, and build the foundations that let us ship fast without breaking things. This is not a traditional QA role. You may review some pull requests and help write e2e tests, but you will ALSO own the monitoring side and build guardrails that scale—all with the goal of preventing and catching issues before customers do. This role combines elements of software engineering, traditional QA, reliability engineering, and devops. What you'll work on:       Observability & Production Health - Design and implement monitoring, alerting, and dashboards so we understand system health at a glance - Own observability for our data pipelines external integrations, and AI workflows - Make sure we know about failures before customers tell us                CI & Test Health                                                                                                                              - Make sure tests consistently run fast and green means green - Maintain staging and test environments that are useful - Help review code with a focus on reliability, edge cases, and failure handling - Build and maintain integration and end-to-end test suites - Close gaps in test coverage by writing tests yourself                 AI Quality & Evals  - Monitor AI workflow correctness and audit individual workflows to catch regressions - Design and maintain eval suites for LLM features - Build a repeatable process for validating prompt changes before they ship

• Review, test, and monitor correctness of features in a fast-moving product that ships to Production *daily* • Create alerts that help us catch issues before they become issues • Monitor AI workflow correctness, audit individual workflows to catch regressions • Make sure tests consistently run super fast • Maintain staging and test environments that are useful • Design and evolve automated tests that meaningfully reduce risk, and help close gaps in test coverage

The basics - The stack: Node.js/Express, Typescript, React, Postgres, Clickhouse, MongoDB, Node.js/Express, Heroku - The product: We're building agentic software for Finance and Operations teams to automate high-volume workflows across systems, from AP and AR to payroll, inventory, and reconciliations. See https://www.woodrow.ai/ - The way we work: - This is a remote job - work anywhere you want, and in any timezone on earth (or outside earth, whatever). - We are an asynchronous team - we don't do scheduled meetings, and rely on each team member to pick their own schedule and to communicate clearly in writing and with recorded videos. Hear from our co-founder Michelle Lee on what it's like to work asynchronously. - We operate completely autonomously - no one will tell you what to do, we'll just tell you the goals and you will figure out how to work towards them with the rest of the team. The role - We’re looking for our first Software Engineer in Test who thinks about quality as a system, not a phase at the end of development. - You’ll work closely with product and engineering to reduce overall bugginess in a fast-moving application where dozens of features and fixes ship daily. - This is not a traditional QA role — you’ll help define what “good” looks like, build guardrails that scale, and make quality visible across the team. You won’t be reviewing and QA’ing every pull request, but instead, adding a layer of QA and creating Production monitoring tools to help fix + prevent issues from ever reaching our customers. What you'll do - Review, test, and monitor correctness of features in a fast-moving product that ships to Production daily - Create alerts that help us catch issues before they become issues - Monitor AI workflow correctness, audit individual workflows to catch regressions - Make sure tests consistently run super fast - Maintain staging and test environments that are useful - Design and evolve automated tests that meaningfully reduce risk, and help close gaps in test coverage Our interview process Our interview process is designed to focus on your skills as a software engineer, and your ability to communicate clearly. We're a fully asynchronous company, so that's how we will communicate in this interview process too 🙂. - We'll ask you to work on ~60 minute coding challenge while recording a Loom (or other screen recording) video of yourself doing the exercise - After reviewing the exercise, we'll ask you to work on a second ~60 minute coding challenge while recording a loom (or other screen recording) video. - If the video interview above goes well, we'll want to learn a bit more about how you communicate in writing - we will ask you to contribute to a technical design document for a new feature, focusing on what system-level tests and monitoring should be built to accompany this feature - Lastly, a short culture-fit interview with our co-founder Michelle. And finally, hopefully we'll send you an offer. And hopefully you'll accept!