DescriptionVerily Pre is a comprehensive, patient-centered platform that accelerates evidence generation for safer, more effective treatments and care decisions. Our cloud-first architecture, advanced analytics, and AI capabilities enable the collection, enrichment, and activation of petabytes of data, tailored to meet the unique needs of our partners.
As Director of Software Development, you will lead a large organization responsible for the core infrastructure powering Verily's AI capabilities and longitudinal health initiatives. You'll oversee the Model Development Lifecycle, accelerate AI production through embedded development partnerships, and deliver critical platforms including Lifelong health studies and Customer Identity and Access Management (CIAM), while shaping technical strategy and fostering a collaborative, results-driven development culture.
Responsibilities- Build and lead a high-performing development organization of 40-50 developers and managers. Define and drive the development culture, performance standards, and collaboration models across multiple cross functional teams.
- Oversee the development strategy for the infrastructure at the core of Verily's Model Development Lifecycle (MDLC), ensuring data scientists have the robust tooling required to prototype, validate, and deploy models efficiently. You will champion the development of annotation and evaluation systems which enable rapid iteration and detect model hallucinations and bias. Additionally you will drive the adoption of foundational model serving infrastructure that enables techniques such as RAG at scale.
- Partner deeply with Data Science, Clinical, and Product leadership to accelerate model development velocity and quality. Translate complex scientific requirements into scalable development roadmaps that support key evidence generation milestones.
- Direct the development of Verily's Lifelong Health Study. Ensuring we seamlessly bridge research and care by capturing high-frequency sensor signals, supporting patient-centric applications like Verily Me, and integrating diverse real-world data streams.
- Own the delivery and reliability of the platform's Customer Identity and Access Management (CIAM) system. Ensure secure, compliant, and seamless access for patients, researchers, and health systems, maintaining our "comply-by-design" philosophy for privacy and data protection.
- Manage organizational resourcing, budgeting, and headcount planning to ensure teams are structured to dependably, sustainably, and quickly deliver on roadmaps. Lead improvements to cross-functional business processes and effectively manage tradeoffs between short-term execution and medium-term architectural investments.
QualificationsMinimum Qualifications
- Bachelor's degree in Computer Science, Engineering, or a related technical field.
- 12+ years of experience in software, data, cloud, or ML engineering roles.
- 5+ years of experience managing development managers and leading technical strategy for multi-team organizations.
- Proven track record of building and leading teams responsible for large-scale data infrastructure, ML platforms, or regulated software products.
Preferred Qualifications
- Master's degree or PhD in Computer Science or a related technical discipline.
- Deep understanding of "ML Ops" and responsible AI practices, including model governance, automated red-teaming, and evaluation frameworks..
- Experience designing and operating Identity and Access Management (IAM/CIAM) systems in a healthcare or highly regulated environment (e.g., HIPAA, GDPR).
- Familiarity with longitudinal health studies, sensor signal processing, and FHIR data standards.
- Demonstrated ability to influence senior leadership (VP+) and drive alignment across engineering, product, and scientific teams.
This role is eligible for Verily-sponsored immigration support.
The Canada base salary range for this full-time position is CAD 207,000 - 233,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
