Director of Software Engineering - Data Platforms - #4919
GRAIL
We are seeking a visionary and execution-focused Director of Software Engineering to lead our Data Platform engineering organization. In this role, you will drive the technical strategy, architecture, and delivery of our next-generation, cloud-native data platform.
The ideal candidate brings over 15 years of software engineering experience, combining deep technical expertise in big data, cloud infrastructure, and AI-driven workflows (including RAG and LLM applications) with a proven track record of scaling engineering teams (10+ headcount). You will collaborate closely with cross-functional executives to translate complex domain requirements into scalable, secure, and compliant production-grade software.
This role is based in Sunnyvale, California. It offers a flexible work arrangement, with the ability to work from GRAIL's office or from home. Our current flexible work arrangement policy requires that a minimum of 60%, or 24 hours, of your total work week be on-site. Your specific schedule, determined in collaboration with your manager, will align with team and business needs and could exceed the 60% requirement for the site. At our Sunnyvale campus, Tuesdays and Thursdays are the key days where we encourage on-site presence to engage in events and on-site activities but candidates must be flexible based on the needs of the business.
Responsibilities
Team Scaling & Culture: Lead, mentor, and scale a multi-disciplinary global engineering organization, fostering a culture of high performance, continuous learning, and technical excellence.
Strategic Roadmap Delivery: Own the technical roadmap and resource allocation, ensuring 95%+ on-time execution of strategic product milestones.
Agile Transformation: Champion and mature Agile/Scrum methodologies to optimize feature velocity, minimize product turnaround time, and maintain high software quality.
Cloud-Native Evolution: Architect, govern, and optimize the transition to modern serverless and microservices architectures on AWS, driving structural cost optimization and system elasticity.
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.
Performance Engineering: Oversee analytical and search data model optimizations to continually improve query performance and data pipeline throughput.
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.
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.
DevOps & SRE Practices: Mature CI/CD automation pipelines using infrastructure-as-code (Terraform, Ansible, Jenkins) to automate provisioning and security patching.
Security & Compliance: Ensure all platforms strictly adhere to modern cybersecurity standards and regulatory compliance frameworks (e.g., GDPR, HIPAA).
Engineering & Organizational Leadership
Strategic Technical Architecture & Data Innovation
AI & Product Modernization
Operational Excellence & Compliance
Required Qualifications
15+ years of progressive experience in software engineering, with 5+ years in a dedicated engineering leadership role managing cross-functional, global teams.
Proven ability to interface with executive stakeholders (Product, UX, Architecture) to align engineering outputs with business growth.
Strong experience managing large operational budgets and implementing strategic cloud cost-optimization practices.
Backend & Architecture: Expert-level knowledge of Java, Spring Boot, Spring MVC, distributed systems design, database sharding, and high-performance microservices.
Data & Analytics: Deep proficiency with Snowflake, Apache Iceberg, AWS Glue, Spark, and Elasticsearch.
AI & Search: Hands-on architecture experience with Retrieval-Augmented Generation (RAG), Large Language Model (LLM) frameworks, and semantic/conversational search.
Cloud & DevOps: Strong expertise in AWS Cloud infrastructure, containerization, and IaC tools (Terraform, Ansible, Jenkins).
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.
Master’s Degree in Computer Science, Software Engineering, or a highly related technical field preferred.
Bachelor’s Degree in Computer Science or Engineering or equivalent practical experience.