About the role
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.
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 redefine how engineers develop, build, test, and deploy software at Scale using AI development tools in addition to traditional practices. 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.
You will
- Define next-generation AI development tooling and frameworks using products like Cursor, Claude Code, OpenAI Codex, and MS Copilot, as well as in-house custom-built solutions.
- Drive the architecture, design, and implementation of our local development process, build, test, continuous integration, and continuous delivery systems, working closely with stakeholders and internal customers to understand and refine requirements.
- Directly mentor software engineers ranging from new grads to experienced engineers.
- Proactively identify opportunities and drive improvements to software development practices, processes, tools, and languages.
- Present technical information to teams and stakeholders, providing guidance and insight on development processes and technologies.
Ideally you’d have
- 8+ years of full-time engineering experience, post-graduation, with experience in build, test, or CI/CD systems.
- Extensive experience defining and evangelizing best-practices for AI development tools, including cost guardrails, security frameworks, and hosting knowledge-sharing sessions, among others.
- Extensive experience in software development and a deep understanding of distributed systems and public cloud platforms (AWS preferred).
- Experience configuring, testing, and enabling MCP servers, AI agents, and other associated systems.