AI Enablement Engineer: Build Agent-Powered Workflows

Scale AI; San Francisco (CA); On-site; USD 180,000 - 225,000; Full time

Benefits offered by this job

Equity-based compensation

Health, dental and vision coverage

Retirement benefits

Learning and development stipend

Generous PTO

Commuter stipend

Job summary

Scale GP, Scale's enterprise Generative AI platform, is building an AI Enablement team to ground AI in real operational workflows and deploy agentic systems that reason over data and take action. You will collaborate 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

Qualifications

• 3+ years of full-time software engineering experience.
• Solid full-stack fundamentals with production ownership of features you've shipped.
• Familiarity with LLMs, embeddings, vector databases, or modern AI data products/tools.
• Exposure to distributed systems and cloud-based architectures.

Responsibilities

• Own full-stack features and projects end-to-end — from design through production deployment — within a larger product area.
• Sample surfaces - Accounting Agents, Finance Copilots, GTM Agents, Agentic Experimentation Platforms.
• Develop reliable backend services in Typescript/Python, work with distributed systems, data pipelines, and AI/ML infrastructure.
• Integrate LLMs, vector databases, and agentic frameworks to power intelligent workflows.
• Ship quickly through tight experimentation loops while maintaining high quality and reliability.

Skills

Full-stack

LLMs knowledge

Distributed systems

Cloud architectures

Data pipelines

Tools

Typescript

Python

Job description

Scale GP, Scale's enterprise Generative AI platform, is building an AI Enablement team to ground AI in real operational workflows and deploy agentic systems that reason over data and take action. You will collaborate 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