Senior Software Engineer II

Responsibilities

• Own and deliver major capabilities within our Discovery Platform, from the interactive experiences our customers use to explore and understand their results, to the backend data systems that store, process, and serve the large and complex scientific datasets that power them.
• See these capabilities through their full lifecycle: design, development, deployment, and ongoing operation.
• Bring genuine curiosity to the science behind the data, working alongside bioinformaticians, biologists, and product teams to deeply understand what our customers are trying to learn from their results and why it matters.
• Collaborate with teams responsible for the ETL pipelines and algorithms that transform raw instrument data into the protein quantification results our customers depend on.
• Lead with ownership. Drive technical design, contribute to architecture decisions, and hold a high bar for security, reliability, and scale.
• Help develop the engineers around you through thoughtful code review, mentorship, and honest technical dialogue.
• Ambitiously embrace AI as a collaborative partner across the software development lifecycle. Promptly and critically evaluate AI-generated work, and explore new ways AI can improve how we build and operate software.

Qualifications

• A minimum of 5 to 7 years of relevant experience in a high-performing software engineering organization.
• A bachelor’s degree in computer science or a related field is required.
• A strong command of Python/FastAPI, React/TypeScript, and AWS cloud services.
• Solid experience with relational databases and an understanding of columnar data stores.
• Familiarity with Parquet and query engines such as AWS Athena is a plus.
• A customer obsessed mindset. Understand that backend code is just as much a part of the customer experience as the interface they interact with.
• A focus on outcomes. Think in terms of impact delivered, not tasks completed. Hold yourself accountable to the difference your work makes for customers and for the business.
• A design approach that considers the full lifecycle of software, including observability and the ability to confidently operate, monitor, and evolve long after it ships.