As a Software Test Engineer II and a member of a dynamic and multi-functional Agile development team, you will be responsible for identifying real-world, user-centric scenarios and workflows and building & executing test automation to ensure their accuracy within our scientific and healthcare suite of products. Additionally, you will be responsible for reporting, tracking, and testing issues discovered during design and development as well as coaching analysts who may possess less experience. To be successful in this role you need a real passion for quality software, dedication to customer happiness, and an ability to work effectively in a matrix organization. You will need a positive attitude, persistence, a love of problem solving, and the ability to communicate with people at all levels of a product development organization.

Clinisys' AI Philosophy:

Building an AI‑first organisation is central to Clinisys’ purpose and the impact we deliver. As a global provider of intelligent diagnostic informatics solutions, we build AI‑enabled, cloud‑based platforms to enhance diagnostic workflows across healthcare, life sciences, and public health. By applying intelligent technology thoughtfully and responsibly, we help laboratories and testing environments operate more effectively, generate meaningful insights at scale, and ultimately support healthier and safer communities. Operating across more than 30 countries, Clinisys expects all colleagues—regardless of role or function—to work confidently with AI‑enabled tools, apply digital and analytical thinking, and continuously adapt as technologies evolve, must drive an AI first sense of purpose and urgency.

Essential Functions

· Designs and executes test cases, both manual and automated, through the appropriate test management tool

· Ensures technical and domain accuracy of content through close collaboration with domain experts

· Analyzes defects, performs root cause analysis, collaborates to resolve, and executes proactive measures to improve overall quality

· Research and utilizes industry, domain, and technology knowledge and trends to improve the overall quality of deliverables

· Reviews technical documentation for accuracy, completeness, and clarity

· All other duties and responsibilities as assigned

Skills needed to be successful

· Proven ability to utilize data, models, methods, and tools to identify, prioritize, implement, and measure quality improvements

· Proficient knowledge of a variety of test automation tools/frameworks

· Understanding of approaches used to identify, prioritize, and mitigate risks to reduce or eliminate potential threats to software quality

• Understanding of the flow of data through systems and the ability to analyze databases through RDBMS queries (SQL)

· Awareness of regulatory requirements and compliance standards (US, UK, EU)

• Excellent attention to detail and follow-up

• Ability to think creatively, identify alternatives, and generate new ideas necessary to achieve a goal

• Ability to represent software workflows, architecture, entities and relationships via different visual and/or language methods

• Ability to perform root cause analysis to identify the most important contributing factor(s) to an issue

• Experience with a variety of AI based tools (Co-pilot, etc.) and the ability to use them in the design, development, and execution of test automation

Required Experience & Education

• Bachelor’s degree in software engineering, mathematics, or related discipline, or equivalent relevant work experience

• 2-5 years’ experience with software development life cycle, software testing methodologies, and quality assurance

• 1+ years’ experience designing, coding, executing, and maintaining test automation of complex workflows using tools such as Selenium, SpecFlow, JMeter, UIPath, etc.

AI Skills Requirement:
Candidates should have a basic understanding of AI/ML concepts and a willingness to learn how AI tools (e.g., TensorFlow, Azure AI) can be applied to enhance software functionality. Exposure to data-driven development is a plus.

· Familiarity with common AI use cases such as Natural Language Processing, Computer Vision, Predictive Analytics, and Generative AI.

· Awareness of responsible AI practices (bias, fairness, ethics, privacy)

· Ability to consume and integrate APIS from AI/ML services

· Experience with data preparation, prompt engineering, and understanding how to monitor AI model performance for accuracy, drift, and explainability.

Preferred Experience & Education

• Knowledge of scientific data software, medical devices, or healthcare software

• Knowledge of Cloud based or mobile application testing

Supervisory Responsibilities

• None