Quality Assurance Engineer

About Us

icetana is a global leader in AI-powered video analytics, delivering real-time anomaly detection solutions to enhance situational awareness and security for critical infrastructure, campuses, smart cities, and large enterprises. Our technology helps clients monitor vast camera networks with AI that highlights abnormal behaviors, dramatically reducing the burden on human operators.

We’d like to maintain our lead, we’d like to level up our Engineering team and Product. If you get excited about Machine Learning, Computer Vision, and if the letters “Q”, “A” and “E2E” spark joy , this might just be the perfect role for you. If you love ensuring rock-solid product quality and building frameworks that help developers ship with confidence, read on.

Role Overview

As a QA Engineer, your mission is to be the guardian of software excellence. You’ll work closely with the engineering team to create robust, reliable, and scalable test systems. Your goal is to empower developers to move fast, without breaking things, by integrating quality at every stage of the development lifecycle.

You’ll help shape and implement a shift-left testing strategy, ensuring that testing is deeply embedded in the development process, not a post-release afterthought. You’ll work on automated test suites, build continuous integration and testing pipelines, and contribute to the broader automation effort.

You’re someone who knows the testing pyramid, has opinions about flaky tests, and a passion for automation that ensures consistent results. You’ll build tools that give visibility into test coverage, performance regressions, and failure trends. And you’ll collaborate with developers to create ad-hoc environments for testing edge cases and complex scenarios.

Key Responsibilities

• Develop and maintain internal QA tools to improve productivity and streamline engineering workflows.
• Automate software quality assurance processes, including CI/CD pipelines, build systems, and infrastructure automation.
• Enhance quality assurance efforts by building test automation frameworks, integrating automated testing into CI/CD, and identifying areas for improvement.
• Advocate for Shift Left testing strategies, integrating testing early in the development lifecycle to improve code quality and reduce defects.
• Implement and promote Test-Driven Development (TDD) practices to ensure code reliability and maintainability.
• Leverage testing tools and frameworks such as Selenium, JUnit, TestNG, PyTest, Jest, and Cypress to enhance automated testing.
• Collaborate with engineering teams to identify pain points in development and propose scalable solutions.
• Document tools, automation processes, and best practices to ensure maintainability and knowledge sharing.‍
• Stay up to date with industry trends and emerging technologies to continuously enhance our development environment.

About You

• Degree qualified in a relevant subject.
• Not a Jerk - no matter how brilliant. We don’t need any Elton Johns or Mariah Careys in this team.
• You’re an advocate for Test Driven Development.
• Are effective at communicating to the team, responding to their frustrations, bug requests, getting them on board with the tools you build.

Why You’ll Love It Here

• You’ll work in a small, fast-moving team where your impact is visible and valued.
  
• You’ll wear multiple hats, from writing tests, scripting deployment checks, to debugging weird edge cases in CI/CD.
  
• You’ll be part of a culture that values continuous learning, cross-functional collaboration, and building with quality in mind.
  
  

Come join us to help shape a world where developers don’t just write code, they write high-quality, production-ready code that scales.

‍The Tech

We have a fairly modern and light-weight software development process. Our tech stack has a number of services deployed in a single docker compose script including C++/Gstreamer for video processing, Py/Pytorch/YOLO/Ultralytics on the AI side, React/TS frontend, Python backend, PG database all running on rack mounted servers with 4x RTX 5000 GPUs in each.

We built a new stack for Facial Recognition and License Plate Recognition in the space of 6 weeks. Our team of only a handful of developers moves fast despite the challenging variety of problems we face when building ML heavy applications.