B2B

remote

Svitla Systems Inc. is looking for an AI Quality Assurance Engineer for a full-time position (40 hours per week) in Poland. Our client is a leading provider of video analysis solutions for loss prevention and security. It offers a cloud-based platform that acts as a hub to analyze the video stream to find the key points of data and create alerts and reports. It provides motion alerts by detecting unusual motion by setting regions of the camera views, and provides alerts when activity happens. It offers a wide range of tools to keep track of important events and history and identify outlying patterns and incidents. The subscription-based software connects the camera footage with the POS data to review all POS transactions. It pairs them with the corresponding real-time video, creating a dashboard of searchable moments. These moments allow filtering by specific incidents like movement in a room, particular purchases, and unusual staff behavior. The company is headquartered in Ottawa, Ontario, with regional representation worldwide, and serves the retail, banking, and restaurant industries.

We are seeking a skilled QA Engineer with a strong background in both manual and automated testing, ideally in the AI space for cloud-based SaaS solutions. This is a hands-on role within a cross-functional AI product team, working closely with ML engineers, data scientists, and developers to ensure product quality across all areas of development.

You’ll work alongside the Development AI Team and other QA team members, where you can shape and implement the technology and product deliverables to drive the product forward. Your primary focus will be testing new and existing AI features, creating and maintaining test plans for the AI Team, and ensuring high quality throughout the development lifecycle. As gatekeepers of quality, you will increase test coverage, optimize testing with strategic approaches, and proactively identify and mitigate quality risks to deliver a reliable product to the customers.

An overlap till 6-7 PM CET is required.

Requirements

5+ years of software testing experience, ideally in the AI space for cloud-based SaaS solutions.
Experience with backend and API testing, including proficiency with test tools such as Postman (manual) and Pytest (automated).
Proven ability to create, update, and review detailed test plans and strategies.
Demonstrate experience leading tests independently, planning and estimating timelines, and being actively involved in development lifecycle discussions
Strong work ethic with a Positive attitude and a Passion for Quality Assurance.
You Thrive at solving problems and enjoy a good challenge, including troubleshooting AI-related testing nuances.
Team Player with Excellent interpersonal and communication skills (written and verbal), working closely with ML engineers, data scientists, developers, and product managers.
Strong analytical skills and attention to detail.
Demonstrates a “can do” attitude and takes ownership of tasks and responsibilities.
Interest in learning new tools and adapting to new technologies or methodologies.
Bachelor of Science Degree or higher education (Computer Science or related field is an asset).

Nice to have

Familiarity with CI/CD environments and cloud platforms (e.g., AWS).
Automated test development experience is a strong asset, especially using Python, Playwright, and Pytest.
Familiarity and understanding of machine learning concepts, AI pipelines, and integrations between AI components and broader systems is a significant advantage; prior testing experience in MLOps or interest in AI beyond mainstream tools is highly valued.

Responsibilities

Proactively lead all testing activities within the AI team, ensuring comprehensive test coverage and quality assurance.
Execute manual and automated functional, non-functional, and regression testing for front and backend components.
Validate that AI models produce accurate, reliable, and unbiased results by testing various edge cases and diverse datasets.
Identify, design, and execute comprehensive test coverage plans, including end-to-end (E2E) tests across environments.
Define and drive the AI team’s automation strategy, including identifying what to automate and how to integrate automated tests into CI/CD pipelines.
Collaborate closely with the development team and product management to understand upcoming features, create test cases, and provide input to uphold quality in the development lifecycle.
Identify, report, and verify defects while proactively managing QA risks and the mitigation plan.
Develop deep expertise in the SaaS platform, viewing it from the perspectives of customers, internal support teams, and customer success managers who set up accounts.
Provide technical guidance to junior QA team members, helping them understand AI-specific testing methodologies.
To identify potential issues, perform creative, exploratory testing, think outside the box, and employ unpredictable methods.
Continuously improve QA processes to enhance efficiency, coverage, and effectiveness.