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Salary: USD 180,000 - 225,000 / annual
Scale GP is an enterprise Generative AI platform providing APIs and infrastructure for knowledge retrieval, inference, evaluation, and intelligent automation. The company powers mission-critical workflows for leading enterprises, helping teams turn complex data and models into reliable, production-ready AI systems.
Scale is building a new AI Enablement team to create the next generation of agent-powered tools that ground AI in real operational workflows. The team's goal is to help internal teams demystify their own workflows, then deploy agentic systems that reason over data, take action, and deliver measurable outcomes. Engineers on this team will use Scale's own platform to solve real business problems internally, then selectively commercialize that same stack for customers.
This is a 0→1 team seeking a sharp, product-minded engineer who thrives in ambiguity, moves fast, and loves building systems from scratch. You'll work closely with product, forward-deployed engineers, data scientists, and applied AI teams to turn real-world problems into scalable production solutions.
Key responsibilities include owning full-stack features and projects end-to-end—from design through production deployment—within a larger product area. Sample surfaces include Accounting Agents, Finance Copilots, GTM Agents, and Agentic Experimentation Platforms. You'll develop reliable backend services in TypeScript/Python, work with distributed systems, data pipelines, and AI/ML infrastructure. You'll integrate LLMs, vector databases, and agentic frameworks to power intelligent workflows, ship quickly through tight experimentation loops while maintaining high quality and reliability, and adapt across the stack to solve real problems end-to-end.
Ideal candidates have 3+ years of full-time software engineering experience with solid full-stack fundamentals and production ownership of shipped features. Familiarity with LLMs, embeddings, vector databases, or modern AI data products is expected, along with exposure to distributed systems and cloud-based architectures. The role values strong product intuition, customer empathy, entrepreneurial mindset, ownership mentality, comfort collaborating across engineering, product, data science, and applied AI teams, and genuine excitement about building agentic systems that make AI useful in the real world.
