Quality Engineer

About Apheris

At Apheris, we are building the future of how AI is applied in pharmaceutical R&D. We enable leading pharmaceutical teams to discover and develop drugs faster. We host the industry’s largest federated data networks for drug discovery AI, spanning co-folding, ADMET, and antibody developability.

Across these networks, models are trained on proprietary industry datasets to achieve higher performance and broader applicability while keeping data control and IP protected. We deliver these superior models through drug discovery applications that enable teams to run them at scale, further customize them, and integrate them into existing R&D workflows.

• AI Structural Biology (AISB) Network: Pharmaceutical companies collaborate in the field of co-folding, structure-based binding affinity predictions and antibody design.
• ADMET Network: Pharmaceutical and biotech companies collaborate to improve small-molecule property prediction and expand into further drug modalities.
• Antibody Developability Network: Pharma partners collaborate to federate historical and purpose-built antibody developability data sets for secure ML training, without data leaving each partner’s environment.

About the role

As a Quality Engineer at Apheris, you will play a key role in ensuring the reliability, security, and performance of our products that power AI in life sciences. Our portfolio includes the Apheris Gateway for building and joining federated data networks, as well as the Apheris Foundry that enables local runs of AI-based drug discovery workflows.

You will work closely with software engineers and data scientists to design and execute testing strategies for complex, distributed, and GPU-intensive systems - from privacy-preserving federated computations running across multiple organizations to scientist-facing UIs / APIs.

You will be responsible for identifying and implementing the best ways to test our products, covering both functional and non-functional requirements (performance, scalability, reliability, security, and usability) to meet the expectations of our high-profile pharmaceutical and life sciences customers.

At Apheris, Quality Engineers don’t just “write tests”.

We expect you to:

• Champion quality-by-design by collaborating with teams on testability, observability, and robust engineering practices from design through release
• Design, implement, and maintain automated test suites spanning different test levels
• Define and enforce quality gates in our CI/CD pipelines to keep feedback loops short and ensure every change meets our quality bar before it reaches customers
• Partner with product, platform, and infrastructure teams to clarify requirements, identify risk early and shape Test Strategies for new features

By helping teams enforce strong quality engineering practices across the entire Software Development Lifecycle, you will be a key contributor to the success of our products and have a direct impact on how organizations build better AI models and data products while securely collaborating on sensitive life sciences data.

What you will do

• Be a champion regarding quality engineering practices
• Be involved in the development of complex features from the beginning by designing Test Strategies and conducting testing sessions to find bugs at early stages
• Write automated test cases at different test levels and coach other developers on that matter
• Contribute to the development of testing frameworks that support the testing process
• Write Pipelines as Code that will implement automatic quality gates to enforce best practices on the SDLC
• Help teams shorten their feedback loops by adopting CI/CD with a DevOps mindset
• Coordinate Release campaigns, helping the engineering team to successfully release our different products
• Facilitate bug grooming and root cause analysis ensuring every defect incident becomes a learning opportunity that continuously strengthens the team's engineering practices

What we expect from you

• 5+ years of relevant working experience or a Bachelor / Master / PhD in Computer Science (or related fields, e.g., Physics, Mathematics, Engineering) and 3+ years of relevant working experience
• Development and/or test automation experience, preferably using Python (other OOP languages are also valued)
• Able to write scripts to automate tedious day-to-day tasks (using Python, Bash or anything you like to script with)
• Experience with non-functional testing (performance, reliability, fault-tolerance)
• Knowledge in CI/CD and DevOps practices with hands on experience creating / maintaining Pipelines as Code
• Knowledge in Containerization (Docker) and Orchestration (Kubernetes) concepts
• Proficient in a UNIX/Linux environment and with Git and Git workflows
• Excellent communication skills (fluent in English, verbal and written) along with the confidence to take ownership of problem
• Genuine interest in working with cutting-edge technology in a fast-paced environment and a young start-up, never leaving continuous learning aside

Nice to have

• Prior exposure to life sciences domain (considered a big plus but not required)
• Experience with Testing Frameworks (e.g., Playwright, Pytest, Pact, REST Assured, Selenium, Cypress - similar tools are valued)
• Experience in Go and / or Vue.js
• Knowledge of cloud providers (e.g., AWS, Azure, GCP, OpenStack) and on-premise setups (e.g., locally hosted Kubernetes via K3s)
• Knowledge in Software Security (e.g., OWASP)
• Knowledge in infrastructure-as-code tools (GitOps, Terraform, Flux)

What we offer you

• Industry-competitive compensation, including early-stage virtual share options
• Remote-first working - work where you work best, whether from home or a co-working space near you
• Great suite of benefits, including a wellbeing budget, mental health benefits, a work-from-home budget, a co-working stipend and a learning and development budget
• Generous holiday allowance
• Office Days at our Berlin HQ or a different European location (3x a year)
• A fun, diverse team of mission-driven individuals with experience across leading organizations and a drive to see AI and ML used for good