GeneDx (Nasdaq: WGS) delivers personalized and actionable health insights to inform diagnosis, direct treatment, and improve drug discovery. The company is uniquely positioned to accelerate the use of genomic and large-scale clinical information to enable precision medicine as the standard of care. GeneDx is at the forefront of transforming healthcare through its industry-leading exome and genome testing and interpretation services, fueled by the world’s largest, rare disease data sets. For more information, please visit www.genedx.com.

SUMMARY

We are seeking a highly experienced and visionary Principal Software Architect to lead the design and development of our software architecture. The ideal candidate will have a deep understanding of software engineering principles, a proven track record of designing scalable and robust systems, and the ability to guide and mentor a team of engineers. This role is critical in ensuring an efficient streamlined workflow for our genetics testing platform.

PREFERRED QUALIFICATIONS:

• Experience with DevOps practices and tools.
• Knowledge of data architecture and database design.
• Familiarity with machine learning and AI technologies.
• Experience in the healthcare or genetics testing industry.

• Architectural Leadership:
• Work with key stakeholders across the company to define and drive the overall architecture strategy, ensuring alignment with business goals and technology standards.
• Lead the design and ensure the correct implementation of scalable, high-performance, and secure software systems tailored for genetic testing.
• Evaluate and recommend tools, technologies, and processes to ensure the highest quality product platform.
• Workflow Design and Automation:
• Design and implement efficient workflow orchestration solutions to streamline production processes.
• Ensure seamless integration of various software components and systems.
• Optimize workflows for performance, reliability, and scalability.
• Data Modeling:
• Design and implement comprehensive data models to support.
• Ensure data models are optimized for performance, scalability, and maintainability.
• Collaborate with data scientists and bioinformaticians to ensure accurate and reliable data representation.
• Best Practices:
• Establish and promote best practices in software development, deployment, and operations.
• Conduct code reviews and ensure adherence to coding standards and best practices.
• Foster a culture of continuous improvement and innovation within the engineering team.
• Technical Leadership:
• Provide technical guidance and mentorship to engineering teams.
• Stay current with emerging technologies and industry trends to drive innovation in genetics testing.
• Communicate complex technical concepts to non-technical stakeholders effectively.