At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI.

At the foundation of these products is the Platform Engineering team. In this role, you will lead the design and development of core data storage, streaming, caching, and indexing platforms and underlying systems. You'll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies.

• Drive the architecture, design, implementation, and reliability of our foundational data platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements.
• Collaborate with cross-functional teams to define, design, and deliver new features.
• Proactively identify opportunities for and drive improvements to current programming practices, including process enhancements and tool upgrades.
• Present technical information to teams and stakeholders, providing guidance and insight on development processes and technologies.
• Provide technical leadership, upholding and upleveling engineering standards across the organization and mentoring junior engineers.

• 8+ years of Full time engineering experience post-graduation, with specialties in Back End systems and large-scale data storage, streaming, and warehousing.
• Extensive experience with database technologies (MongoDB, Postgres), streaming/processing solutions (Kinesis, Flink, Spark), indexing/caching (ElasticSearch, Redis), and data query engines (Trino, Presto, Snowflake).
• Track record of mentoring and leading teams on successful projects.
• Excellent communication and collaboration skills, able to translate complex technical concepts to non-technical stakeholders.
• Fluent with containerization & deployment technologies like Kubernetes and public cloud platforms.
• Deep understanding of distributed systems, cloud platforms and data systems.
• Experience driving cross-functional collaboration and communication at an organizational level.

• Strong knowledge of software engineering best practices and CI/CD tooling (eg, CircleCI).
• Performance tuning and cost optimizations of cloud-based data platforms.
• Defining a data lifecycle strategy and designing/implementing tooling for data privacy (eg, GDPR).
• Experience scaling products at hyper-growth startups.
• Excitement to work with AI technologies.

Compensation packages include base salary, equity, and benefits. Base salary for this Full time position in the locations of San Francisco, New York, Seattle ranges from $248,400 - $310,500 USD. Equity compensation is subject to Board of Director approval.

Benefits include comprehensive health, dental, and vision coverage; retirement benefits; a learning and development stipend; generous paid time off; and a commuter stipend (potentially).

We have a 90-day waiting period before reconsidering candidates for the same role, to ensure a fair and thorough evaluation of all applicants.

We believe that everyone should be able to bring their whole selves to work. We are proud to be an inclusive and equal opportunity workplace and are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity, or veteran status. We are committed to providing reasonable accommodations to applicants with physical or mental disabilities. If you need assistance, please contact us at (see below) We collect and use personal data for professional purposes in accordance with applicable laws and our privacy policy.

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide high-quality data and full-stack technologies that power leading models and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact.