Director, Data Platform Engineering

Lila Sciences, Inc.
San Francisco, United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Compensation
$300,000.0
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Amazon Web Services Amazon S3 Big Data BigQuery Encodings Information Engineering Data Infrastructure Python (Programming Language) Machine Learning Software Engineering Data Streaming
+17 more
Data Processing Data Server Interface Data Ingestion Large Language Models Backend Data Strategy Containerization Kubernetes Storage Technologies Information Technology Apache Flink Apache Kafka Data Management Data Lakehouse Vertica Software Coding Data Pipelines

Job description

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 30-40 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.

Requirements

  • 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.

Benefits & conditions

We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.

U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.

International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market. Expected Base Salary Range $300,000-$390,000 USD

About the company

Lila Sciences is building Scientific Superintelligence to solve humankind’s greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.

LILA combines advanced AI models with proprietary AI Science Factory instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.

Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you’d love to work in, even if you don’t meet every qualification listed above, we encourage you to apply.

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