Director of Software Engineering - Data Platforms - #4919

Grail•Sunnyvale, CA

1d•Hybrid

About The Position

GRAIL is seeking a visionary and execution-focused Director of Software Engineering to lead their Data Platform engineering organization. This role will drive the technical strategy, architecture, and delivery of their next-generation, cloud-native data platform. The ideal candidate will have over 15 years of software engineering experience, with deep technical expertise in big data, cloud infrastructure, and AI-driven workflows (including RAG and LLM applications), and a proven track record of scaling engineering teams (10+ headcount). The position involves close collaboration with cross-functional executives to translate complex domain requirements into scalable, secure, and compliant production-grade software. This role is based in Sunnyvale, California, and offers a flexible work arrangement with a requirement for a minimum of 60% (24 hours) of the work week to be on-site.

Requirements

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.
Expert-level knowledge of Java, Spring Boot, Spring MVC, distributed systems design, database sharding, and high-performance microservices.
Deep proficiency with Snowflake, Apache Iceberg, AWS Glue, Spark, and Elasticsearch.
Hands-on architecture experience with Retrieval-Augmented Generation (RAG), Large Language Model (LLM) frameworks, and semantic/conversational search.
Strong expertise in AWS Cloud infrastructure, containerization, and IaC tools (Terraform, Ansible, Jenkins).
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.

Nice To Haves

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

Responsibilities

Lead, mentor, and scale a multi-disciplinary global engineering organization, fostering a culture of high performance, continuous learning, and technical excellence.
Own the technical roadmap and resource allocation, ensuring 95%+ on-time execution of strategic product milestones.
Champion and mature Agile/Scrum methodologies to optimize feature velocity, minimize product turnaround time, and maintain high software quality.
Architect, govern, and optimize the transition to modern serverless and microservices architectures on AWS, driving structural cost optimization and system elasticity.
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.
Oversee analytical and search data model optimizations to continually improve query performance and data pipeline throughput.
Direct the integration of AI-assisted SDLC tools and architect LLM-enabled product features, including RAG-based semantic search and conversational search workflows.
Oversee the development of high-throughput ETL pipelines and secure, scalable RESTful APIs built on Java / Spring Boot to ensure global data interoperability.
Mature CI/CD automation pipelines using infrastructure-as-code (Terraform, Ansible, Jenkins) to automate provisioning and security patching.
Ensure all platforms strictly adhere to modern cybersecurity standards and regulatory compliance frameworks (e.g., GDPR, HIPAA).