Staff Data Platform Engineer — LLM Data Engine Lead

Scale AI, Inc.; San Francisco (CA); On-site; USD 252,000 - 315,000; Full time

Job summary

Scale AI, Inc. is seeking a senior Platform Engineer to lead the design and development of core data storage, streaming, caching, and indexing platforms. You will drive reliability and work with stakeholders to refine requirements while mentoring junior engineers.

The role involves collaborating across teams to implement new features, improve processes, and uplevel engineering standards in a rapidly evolving AI data environment.

Qualifications

• 8+ years of full-time engineering experience post-graduation in backend/data platforms.
• Proven ability to architect large-scale data storage, streaming and warehousing systems.
• Experience mentoring teams and leading cross-functional projects.
• Strong communication and collaboration skills with non-technical stakeholders.
• Fluency with containerization and public cloud deployments using Kubernetes.

Responsibilities

• Lead architecture, design, implementation and reliability of core data platforms.
• Collaborate with cross-functional teams to define and deliver features.
• Identify opportunities to improve programming practices and tooling.
• Present technical information and guide development processes.
• Provide technical leadership and uplift engineering standards across the org.

Skills

Backend systems

Data storage

Streaming

Warehousing

MongoDB

Postgres

Kinesis

Flink

Spark

ElasticSearch

Redis

Trino

Presto

Snowflake

Mentoring

Team leadership

Communication

Kubernetes

Cloud platforms

Tools

Kubernetes

CircleCI

Job description

Scale AI, Inc. is seeking a senior Platform Engineer to lead the design and development of core data storage, streaming, caching, and indexing platforms. You will drive reliability and work with stakeholders to refine requirements while mentoring junior engineers.

The role involves collaborating across teams to implement new features, improve processes, and uplevel engineering standards in a rapidly evolving AI data environment.