Senior Software Engineer, Bioinformatics (Rust & Python)

About Variantyx:

Join our rapidly growing, engineering-driven organization and help build the software that powers the future of whole-genome diagnostics. Backed by leading life sciences investors, we have achieved industry-leading diagnostic yield and unit economics through a vertically integrated software stack that spans from sample to report. At the core of our success is a proprietary clinical platform that uniquely enables our workflows, allowing us to solve complex biological data challenges at scale. With a strong global presence across our internal teams and external partnerships, we offer the stability of a well-funded industry leader combined with the agility of a high-growth tech company.

About the Position:

We are looking for an experienced, production-focused Senior Software Engineer to lead the architectural evolution of our core germline clinical bioinformatics pipeline.

Our production pipeline is a large-scale, high-throughput system. We continue to push the frontier of diagnostic capabilities while heavily scaling our operations. As part of a lean, high-caliber engineering team, you will take ownership of complex technical challenges, delivering clean, rigorously tested, and heavily optimized code.

This is strictly a production software engineering role, not an academic research, data science, or scripting position. We are specifically looking for highly technical engineers with a strong Computer Science background who build robust, high-performance systems. If your primary experience is writing R or Python scripts for data analysis or academic research, this role will not be a fit.

What You Will Do:

• High-Performance Engineering: Identify bottlenecks and rewrite/optimize core primary, secondary, and tertiary bioinformatics pipelines utilizing Rust for maximum performance and memory safety.
• Systems Integration: Seamlessly bridge high-performance Rust modules with our existing Python infrastructure using tools like PyO3 and Maturin.
• Database Architecture: Design, implement, and scale complex database schemas (MongoDB and RDBMS) to manage massive, high-throughput genomic datasets efficiently.
• Clinical-Grade Feature Development: Design, develop, validate, and deploy cutting-edge algorithms for variant detection and scoring on our high-performance CPU and GPU compute clusters.
• Production Quality Assurance: Enforce strict software quality standards, SDLC best practices, and automated testing to ensure our clinical results are perfectly accurate and reproducible in a highly regulated environment.

Required Qualifications:

• Education & Experience: Master’s or Bachelor’s degree in Computer Science, Software Engineering, or a closely related technical field, backed by 5+ years of dedicated industry experience in production software engineering.
• Rust & Python Expertise: You are an expert in both Rust and Python. You understand Python internals, packaging, and design patterns, and you are highly proficient in writing memory-safe, concurrent Rust code (including Python extensions).
• Database Architecture: Strong background in database design, data modeling, and performance tuning. You have deep experience with MongoDB, relational databases (RDBMS), normalized schemas, and complex data migrations.
• Production Engineering Rigor: You do not write “scripts”; you build systems. You have deep expertise in the Software Development Lifecycle (SDLC), testing frameworks, mocking strategies, and writing modular, deployable code.
• Bioinformatics Domain Knowledge: Strong production experience working with standard genomic file formats (FASTQ / BAM / CRAM / VCF), variant calling algorithms, and high-throughput sequencing platforms (short- and long-read).
• Linux/Bash Mastery: You are highly comfortable debugging complex systems interactions in a Linux environment and writing robust shell automation.

Preferred Qualifications:

• Advanced Degree: PhD in Computer Science, Software Engineering, or closely related field.
• Typescript: Experience writing Typescript to interface with our MongoDB data layer and execute workflows.