Director of Software Engineering - Data Platforms - #4919

Our mission is to detect cancer early, when it can be cured. We are working to change the trajectory of cancer mortality and bring stakeholders together to adopt innovative, safe, and effective technologies that can transform cancer care.

We are a healthcare company, pioneering new technologies to advance early cancer detection. We have built a multi-disciplinary organization of scientists, engineers, and physicians and we are using the power of next-generation sequencing (NGS), population-scale clinical studies, and state-of-the-art computer science and data science to overcome one of medicine’s greatest challenges.

GRAIL is headquartered in the bay area of California, with locations in Washington, D.C., North Carolina, and the United Kingdom. It is supported by leading global investors and pharmaceutical, technology, and healthcare companies.

For more information, please visit grail.com

Responsibilities

Engineering & Organizational Leadership

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Team Scaling & Culture: Lead, mentor, and scale a multi-disciplinary global engineering organization, fostering a culture of high performance, continuous learning, and technical excellence.

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Strategic Roadmap Delivery: Own the technical roadmap and resource allocation, ensuring 95%+ on-time execution of strategic product milestones.

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Agile Transformation: Champion and mature Agile/Scrum methodologies to optimize feature velocity, minimize product turnaround time, and maintain high software quality.

Strategic Technical Architecture & Data Innovation

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Cloud-Native Evolution: Architect, govern, and optimize the transition to modern serverless and microservices architectures on AWS, driving structural cost optimization and system elasticity.

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Big Data Ecosystems: Define the strategy for next-generation big data platforms utilizing Snowflake, Databricks, Apache Iceberg, AWS Glue, etc. to process, partition, and index petabyte-scale datasets.

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Performance Engineering: Oversee analytical and search data model optimizations to continually improve query performance and data pipeline throughput.

AI & Product Modernization

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AI-Driven Initiatives: Direct the integration of AI-assisted SDLC tools and architect LLM-enabled product features, including RAG-based semantic search and conversational search workflows.

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API & System Interoperability: Oversee the development of high-throughput ETL pipelines and secure, scalable RESTful APIs built on Java / Spring Boot to ensure global data interoperability.

Operational Excellence & Compliance

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• DevOps & SRE Practices: Mature CI/CD automation pipelines using infrastructure-as-code ( Terraform, Ansible, Jenkins ) to automate provisioning and security patching.
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• Security & Compliance: Ensure all platforms strictly adhere to modern cybersecurity standards and regulatory compliance frameworks (e.g., GDPR, HIPAA ).

Required Qualifications

Leadership & Soft Skills

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• 15+ years of progressive experience in software engineering, with 5+ years in a dedicated engineering leadership role managing cross-functional, global teams.
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• Proven ability to interface with executive stakeholders (Product, UX, Architecture) to align engineering outputs with business growth.
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• Strong experience managing large operational budgets and implementing strategic cloud cost-optimization practices.

Technical Stack & Domain Expertise

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Backend & Architecture: Expert-level knowledge of Java, Spring Boot, Spring MVC , distributed systems design, database sharding, and high-performance microservices.

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Data & Analytics: Deep proficiency with Snowflake, Apache Iceberg, AWS Glue, Spark, and Elasticsearch .

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AI & Search: Hands-on architecture experience with Retrieval-Augmented Generation (RAG) , Large Language Model (LLM) frameworks, and semantic/conversational search.

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Cloud & DevOps: Strong expertise in AWS Cloud infrastructure , containerization, and IaC tools (Terraform, Ansible, Jenkins).

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Domain Interoperability: Experience in high-volume, regulated data fields (e.g., genomics, healthcare, bioinformatics, or fintech) and data standards (e.g., GA4GH) is highly desirable.

Education

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• Master’s Degree in Computer Science, Software Engineering, or a highly related technical field preferred.
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• Bachelor’s Degree in Computer Science or Engineering or equivalent practical experience.