Our client is a B2B SaaS platform operating at the intersection of data intelligence and LinkedIn advertising. The product is in active growth — the engineering team ships continuously, and feature velocity is high. The platform combines LinkedIn Ads optimization, website visitor identification, and revenue attribution in one decision layer — so marketers can see which companies engage with their ads, connect that activity to CRM data, and prove what actually drives deals.
The team is small and senior: a product manager, 3 backend engineers (PHP/Laravel), 1 frontend engineer (React), and 3 data engineers (Python, N8N), on AWS-managed infrastructure with Postgres and Clickhouse. The team works in sprints with sprint planning and retrospectives.
Why this role exists
Two gaps are holding the team back. First, the CTO is absorbing too much coordination overhead: breaking down requirements, running syncs, unblocking developers. Second, testing coverage hasn’t kept pace with shipping speed — bugs that automated tests would have caught are slipping through to production.
This role is designed to close both gaps at once. The PM side frees up the CTO by owning task creation and team coordination. The QA side builds an automated testing layer from scratch, with AI tooling at its core. Neither half of this role is a full-time job on its own — together, they’re exactly one.
What you’ll own
Project management — primary focus * Receive requirements from the CTO and convert them into detailed, developer-ready tasks and epics in ClickUp, following the company’s established task framework * Run sprint planning and retrospectives, keep the team unblocked, and handle routine coordination without escalating to the CTO * Own documentation: maintain clear, up-to-date technical specs and requirement breakdowns * Be the connective tissue between product intent and engineering execution — understand the business logic behind what’s being built, not just the task list * Track progress, flag risks early, and make sure work that gets decided actually gets finished
QA automation — secondary focus * Build an automated QA framework from scratch — end-to-end, regression, and API testing; choose your own tools and programming language * Triage and classify bugs by root cause (frontend vs. backend) before routing to developers * Write test plans and document edge cases; build coverage that actually prevents regressions, not just documents them
Requirements
What we expect from an ideal candidate * 3–5 years of total experience with at least 1.5 years in a project or product management role and at least 1.5 years in QA engineering * At least 2 years of that experience must be at a product company * Proven ability to break down product requirements into clear, structured technical tasks for a development team * Experience running sprint planning and retrospectives, or working closely within that process * Strong self-management and prioritization — able to hold multiple threads across PM and QA without dropping things or waiting to be told what’s next * Experience in QA engineering with a demonstrated shift toward automation — manual-only QA is not a fit for this role * Solid understanding of regression testing and functional testing concepts * Working knowledge of SQL sufficient to validate data at the database level (Postgres, Clickhouse a plus) * Ability to distinguish frontend bugs from backend bugs quickly and describe them precisely * You should be actively using AI tools to automate, build, and accelerate your own workflow * English B1 or above — sufficient for written communication and technical documentation
Nice to have * B2B SaaS background in a QA, PM, or hybrid role * Prior experience with a marketing technology product (attribution, analytics, ad tech, CRM, or similar) * Strong English (C1) — a plus for communication with native-speaking stakeholders
What to expect from the company * Investment in your growth — the company is willing to develop this person into a stronger PM and a more capable user of AI tooling, not just hire for what exists today * An established process framework to work within (ClickUp, sprints) that you can improve over time * Direct access to decision-makers in a flat, fast-moving structure * Freedom to choose your own QA tooling and programming language — no mandated stack on the testing side
Interview process * Recruiter screen * Interview with the CTO * Test task * Final round
To help us review your application efficiently, please answer three short questions in the cover letter. There are no right or wrong answers — we’re looking for clarity and specifics, not length.
1. Describe a product or feature you managed from brief to release. What broke along the way, and what did you do about it?
2. Walk us through a QA automation framework you built or meaningfully improved. What was the coverage before and after, and what stack did you use?
3. Show us a specific example of how AI tools changed the way you work — a workflow, a test, a process, or a decision that you handle differently because of AI. What tool, what task, what result?
Applications without answers to these questions will not be reviewed.
