Director, Data Platform Engineering

Location: San Francisco, CA USA

Department: Software

Your Impact at Lila

Lila is seeking a highly motivated and experienced engineering leader to lead a team responsible for our Lila's product data platform. You will own the data platform and infrastructure end-to-end — architecture, delivery, reliability, and developer/data scientist experience.

Our mission is to deliver Scientific Super Intelligence through a reliable, scalable, and self-service infrastructure for data ingestion, storage, processing, and interaction — enabling AI/ML, product teams, and scientists to build data-intensive applications with confidence and speed. Our platform supports analytical and machine learning workloads across Lila, serving autonomous DBTL cycles, instrument data pipelines, and AI inference workflows.

You will be responsible for building and leading a team of talented engineers, driving technical strategy, and ensuring the scalability and performance of our data management and data serving capabilities of our Data Platform. You will work closely with data scientists, data engineers, lab scientists, and product teams to understand their needs and deliver innovative solutions that leverage the power of cutting edge data processing technologies.

What You'll Be Building

• Team Leadership: Build, mentor, and manage a high-performing team of 8-12 data engineering experts. Evaluate and adopt modern data infrastructure - including real-time streaming (Kafka, Flink), columnar engines (DuckDB, ClickHouse), lake house, and cloud-native object storage architectures; Foster a culture of collaboration, innovation, and continuous improvement; Provide technical guidance and mentorship to team members, promoting their professional growth; Conduct performance reviews, provide feedback, and identify opportunities for training and development; Manage team workload, prioritize projects, and ensure timely delivery of high-quality solutions.
• Technical Strategy and Execution: Define and execute the technical roadmap for our data platform, aligning with Lila’s overall data strategy; Drive innovation in data Lakehouse and data serving ecosystem exploring new technologies and approaches to improve usability, performance, scalability, and efficiency; Ensure the reliability, availability, and security of our data processing infrastructure.; Collaborate with other engineering teams to integrate our data processing technologies with other Lila systems and services.
• Stakeholder Management: Partner with data scientists, data engineers, lab scientists, product managers, and other stakeholders to understand their data processing needs and requirements; Communicate technical concepts and solutions effectively to both technical and non-technical audiences; Advocate for best practices in data processing and engineering; Manage expectations and ensure alignment across different teams.
• Engineering Thought Leadership: Represent Lila’s data platform work at external conferences; Deliver presentations, and write blog posts highlighting Lila’s leadership in big data processing.
• Scientist and Engineering Productivity: Drive innovative, agentic, and low-code solutions to deliver data interfaces - exploration, query, analytics, and ML/inference solutions at scale.

What You’ll Need to Succeed

• 12+ years of software development experience, with a focus on data processing at scale. 5+ years of experience leading senior engineers.
• Experience with building on AWS/GCP primitives like S3 + Athena/BigQuery, and query engines.
• Operated data platforms at petabyte scale with sub-second query latency requirements.
• Experience managing data infrastructure supporting 100+ concurrent ML training and inference workloads.
• Familiarity with LLM/AI-native data patterns — vector stores, embedding pipelines, pre/mid/post training.
• Track record of building data platforms in high-growth or early-stage environments where speed-to-value mattered as much as long-term architecture.
• Hands-on coding in Python and modern backend frameworks. Experience with infrastructure-as-code and containerized deployments (Kubernetes).
• BS, MS, or Ph.D. in Computer Science or a related field of study.

Bonus Points For

• Thought leadership in the community via presentations in conferences or blog posts.
• Experience building and growing teams focusing on open source technologies.
• Scientific data management and quality experience
• Built self-service data products/platforms where developer experience was a first-class product concern.

About Lila

Lila Sciences is the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science.  We are pioneering a new age of boundless discovery by building the capabilities to apply AI to every aspect of the scientific method.  We are introducing scientific superintelligence to solve humankind's greatest challenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. Learn more about this mission at  www.lila.ai

If this sounds like an environment you’d love to work in, even if you only have some of the experience listed below, we encourage you to apply.

We’re All In

Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.

A Note to Agencies

Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.