About the job
Scale GP is Scale’s enterprise Generative AI platform, providing APIs and infrastructure for knowledge retrieval, inference, evaluation, and intelligent automation. We power mission-critical workflows for leading enterprises by helping teams turn complex data and models into reliable, production-ready AI systems. We’re forming a new Agentic Data Products team focused on building the next generation of agent-powered tools that ground AI in real operational workflows. Our goal is to help enterprises demystify their data layers and deploy intelligent, agentic systems that can reason over data, take action, and deliver measurable outcomes. This is a 0→1 build team. We’re looking for a sharp, product-minded Senior Engineer who thrives in ambiguity, moves quickly, and enjoys building new systems from scratch alongside customers and cross-functional partners. You’ll work closely with product, forward-deployed engineers, data scientists, and applied AI teams to turn real-world problems into scalable, production solutions. If you like shipping fast, owning outcomes, and working across the stack—from polished frontends to distributed backends to LLM integrations—this role is for you.
Responsibilities
Own major full-stack product areas, driving features from concept and design through production deployment
Build intuitive, high-performance frontend experiences using React + TypeScript
Develop reliable backend services in Python, working with distributed systems, data pipelines, and AI/ML infrastructure
Integrate LLMs, vector databases, and agentic frameworks to power intelligent workflows and decision-making systems
Ship quickly through tight experimentation loops while maintaining high quality and reliability
Help define the technical direction and architecture of a brand-new team and product surface
Adapt across the stack and learn new tools as needed to solve real problems end-to-end
Qualifications
Minimum
5+ years of full-time software engineering experience
0-1 product build experience
Preferred
Familiarity with LLMs, embeddings, vector databases, or modern AI data products/tools
Experience with distributed systems and cloud-based architectures
Prior experience mentoring or leading team