Builder QA II

• *Job Description**

You are an engineer who specialises in proving things work. The distinction between “dev” and “QA” work is not one we maintain: you read the application code, you write production\-grade Python, and you build agents. The difference is what you point them at.

1\. Core DNA

• **AI\-Native Workflow.** You use AI to accelerate everything you do as a default, not an experiment. You have opinions about which tools earn their place.
• **Agentic Implementation.** You build, debug and deploy autonomous agents — LLM\-driven test generation, Playwright browser\-use agents, self\-healing locator strategies — against complex ERP screens and workflows.
• **Legacy\-to\-Modern Bridge.** Some of what you’ll test is a modern web rewrite. Some is a desktop application older than your career. Both are puzzles.
• **Evidence Over Confidence.** A generated test that has never been executed is not a test. You know your own false\-positive and flake rates rather than claiming there aren’t any.

2\. What You Own

• *The ticket\-to\-test pipeline.** An agent that reads a requirement or defect, understands the affected area, and produces a real test — grounded in the actual application, not in what the model imagines the application looks like. Hallucinated locators are the failure mode that kills these systems; preventing them is your problem.

• *Execution and stabilization.** Generation is the easy half. Your pipeline isn’t done when a test file exists or a ticket gets created — it’s done when the test has run against a real build, passed repeatedly, and earned its place in the suite. Flake is the enemy, because a suite nobody trusts is worse than no suite.

• *Coverage that means something.** You can tell the difference between a suite that covers the code and a suite that covers the risk. You use mutation testing and real defect history rather than counting tests, and you argue for the edge cases that actually bite: fiscal calendars, multi\-currency, partial shipments, period\-end adjustments.

3\. Where You Might Lean In

• **Test Generation \& Grounding** — the retrieval and context problem. How does an agent know what the screen really contains, what the business rule really is, and what changed in this release?
• **Adversarial \& Red\-Team** — you build agents whose job is to break things. Programmatic prompt optimization (DSPy), fuzzing business logic, hunting the input nobody thought of.
• **Test Infrastructure \& Agent\-Ops** — the factory the test agents run in: parallel execution, environment and data management, tracing, and the observability to know why a run went sideways.
• **Legacy Surface Automation** — desktop and thick\-client applications where modern tooling doesn’t reach and the automation has to be built rather than installed.

What You’ll Actually Do

• **Build test\-generation agents** that take a ticket and produce an executable test grounded in the live application.
• **Close the loop.** Make generation, execution, stabilization and reporting one pipeline rather than four disconnected steps with a human carrying work between them.
• **Automate the untestable.** Wrap legacy business logic — the modules everyone has avoided because there’s no spec — in characterization tests that capture what the system actually does today.
• **Kill flake.** Find the root cause rather than adding a retry. Retries are how suites die.
• **Red\-team the financial logic.** Build the agents that go looking for the case where the ledger doesn’t balance.
• **Fix your own agents in production.** Read the traces, find why it went sideways, make it not happen again.

What Good Looks Like

• (Illustrative — real targets agreed with the hiring manager.)*

• **30 days:** Shipped your first agent\-generated test into a running suite — generated, executed, stable.
• **90 days:** Owning the ticket\-to\-test pipeline for a product area end to end, with a measured flake rate and a real coverage picture.
• **6 months:** Other Builders reuse what you built. Escaped defects in your area are measurably down, and you can show why.

The Stack

Python, pytest, Playwright, SQL (Postgres/SQL Server), TypeScript, OpenAI/Anthropic, LangChain/LangGraph, DSPy, pgvector/Qdrant, Docker, CI/CD pipelines, OpenTelemetry, eval and tracing platforms (LangSmith / Langfuse / Braintrust or equivalent), desktop automation frameworks where the application demands it. And any other tool that helps us achieve greatness.

Who You Are

• **You’ve shipped one.** You have built at least one autonomous agent or complex LLM workflow that real people used for real work — not a weekend demo. You know how it failed, because it did.
• **You write real code.** Python that goes to production and gets reviewed like anyone else’s. If your automation experience stops at a record\-and\-playback tool, this isn’t the role.
• **The manual\-task hater.** You have a physical reaction to repetitive work. If you do it twice, you’ve already started drafting the automation.
• **Technically fearless.** A 500\-table undocumented legacy schema isn’t complexity, it’s a puzzle about to get solved. You aren’t intimidated by spaghetti code — you’re the one who brings the sauce.
• **Rigor over hype.** You love the new models and you still ask for the numbers. You know the difference between a cool demo and a pipeline people rely on every release.
• **Suspicious by instinct.** Your first question about any green build is what it didn’t check.

Why Join Us

• **Quality is engineering here, not a stage gate.** You are a Builder on the same ladder, with the same levels and the same expectations as everyone else in the squad. You build; you don’t sign off on other people’s work.
• **The Final Boss of complexity.** ERPs are the ultimate challenge for AI. If you can build agents that validate a General Ledger, you’ve solved the hardest version of this problem.
• **Agentic autonomy.** We don’t do tickets. We do missions. You’ll have real freedom over the models, frameworks and agent architectures you think will win.
• **No red tape.** If the agent works and the evals pass, we ship. No Change Management Committee — a “Does It Work?” policy.
• **The Builder Tribe.** You won’t be the only AI person in the room. You’ll be part of a small squad equally obsessed with moving faster, where your automation hacks are your biggest contribution rather than a hidden side project.