Engineering Manager, GenAI
ScaleSan Francisco, CA; New York, NYPosted 20 February 2026
Job Description
At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations.
About Data Engine
Our Generative AI Data Engine powers the world’s most advanced LLMs and generative models through world-class agentic data, 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.
Responsibilities:
Manage the engineering team and drive technical delivery
Comfortable working cross functionally, whether that be internal or external customers
Work across the entire product lifecycle from conceptualization through production
Build features end-to-end: front-end, back-end, system design, debugging and testing
Deliver experiments at a high velocity and level of quality to engage our customers
Influence the culture, values, and processes of a growing engineering team
Inspire and mentor engineers
Collaborating with cross-functional teams to define, design, and ship new product features and experiences
Requirements:
At least 5 years of relevant experience as a Full Stack Product Engineer and at least 2 years of experience managing engineers is preferred
Experience in Java, Python, Javascript, and React
Proven success in leading, managing, and developing high-performing Engineering teams
Expertise in identifying product engagement patterns and trends for large scale consumer products
Track record of shipping high-quality products and features at scale
Desire to work in a very fast-paced environment
Ability to turn business and product ideas into engineering solutions
Excellent problem-solving skills, and be able to work independently or as part of a team.
Excited to join a dynamic, hybrid team in either San Francisco or New York City.
Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.
Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:
$216,200
$270,250 USD
PLEASE NOTE:
Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
About Us:
At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely wit ... (truncated, view full listing at source)
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