Staff Software Engineer, Data Platform

Scale AI, Inc.; New York (NY); On-site; USD 252,000 - 315,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Retirement benefits

Learning stipend

Paid time off

Commuter stipend

Job summary

Scale AI, Inc. is building foundational data platforms and offering a chance to lead their storage, streaming, caching, and indexing systems. You will shape architecture, raise engineering standards, and mentor engineers across the organization while engaging with cutting-edge AI initiatives.

The role requires deep backend expertise, distributed data thinking, and strong collaboration across teams. You will operate in a fast-growing AI enablement environment and influence scalable data solutions.

Qualifications

• 8+ years of full-time engineering experience in backend systems for large-scale data storage, streaming, and warehousing.
• Experience with MongoDB, Postgres, Kinesis, Flink, Spark, ElasticSearch, Redis, and query engines like Trino/Presto/Snowflake.
• Experience mentoring and leading engineering teams.
• Strong communication and collaboration skills.
• Fluent with Kubernetes and public clouds.
• Deep understanding of distributed systems, cloud data platforms.
• Experience driving cross-functional collaboration.

Responsibilities

• Drive architecture, design, and reliability of core data platforms and systems.
• Collaborate with cross-functional teams to define and deliver features.
• Identify opportunities to improve engineering practices and tooling.
• Present technical information to stakeholders and provide guidance.
• Provide technical leadership and mentor junior engineers.

Skills

Senior backend engineering

Distributed systems

Cloud platforms

Containerization (Kubernetes)

Data storage & warehousing

Mentoring & leadership

Communication

Tools

MongoDB

Postgres

Kinesis

Flink

Spark

ElasticSearch

Redis

Trino/Presto

Snowflake

Job description

Software is eating the world, but AI is eating software. We live in unprecedented times - AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human evaluation and reinforcement learning through human feedback (RLHF) during pre‑training, fine‑tuning, and production evaluations. This is the main innovation that has enabled ChatGPT to get such a large head‑start among competition.

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.

Responsibilities

• 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 driving 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, including upholding and upleveling engineering standards across the organization, mentoring junior engineers.

Qualifications

• 8+ years of full‑time engineering experience, post‑graduation with specialties in back‑end systems, specifically related to building large‑scale data storage, streaming, and warehousing systems.
• Extensive experience in various database technologies (MongoDB, Postgres), streaming/processing solutions (Kinesis, Flink, Spark), indexing/caching (ElasticSearch, Redis), and various data query engines (Trino, Presto, Snowflake, etc.).
• Show a track record of mentoring and leading teams in successful projects.
• Possess excellent communication and collaboration skills, and the ability to translate complex technical concepts to non‑technical stakeholders.
• Experience working fluently with standard containerization & deployment technologies like Kubernetes and various public cloud offerings.
• Extensive experience in software development and a deep understanding of distributed systems, cloud platforms and data systems.
• Experience driving cross‑functional collaboration and communication at an organizational or broader level.

Nice to Haves

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

Compensation and Benefits

Compensation packages include base salary, equity, and benefits. The salary range for this full‑time position in the locations of San Francisco, New York, and Seattle is $252,000 – $315,000 USD. Additional benefits include comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, generous paid time off, and a commuter stipend. This role may also be eligible for additional benefits such as a commuter stipend.

Equal Employment Opportunity

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We 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 working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [e-mail]. Please see the United States Department of Labor's Pay Transparency provision.

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