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Finalroundai

AI Engineer — Learn Engine: Platform & Simulation

Finalroundai

Location
Onsite (San Francisco, California)
Employment
Full-time
Level
Senior Level
Posted 1 week ago

About the Role

Build innovative tools like a campaign simulator and creative intelligence engine to create a competitive advantage. You will work alongside intelligence engineers to develop a closed-loop optimization system that improves with every dollar spent.

Skills

TypeScript Python Browser Automation Simulation Infrastructure Experimentation Infrastructure LLM Orchestration Computer Vision Probabilistic Modeling Monte Carlo Simulation Product Design AI Development Image Analysis

Full job details

Build the tools that do not exist yet — a campaign simulator, a creative intelligence engine, an experimentation platform. This is invention work, not integration work. Every tool you build becomes a product moat that competitors cannot easily replicate. You will work alongside the intelligence engineer to create a closed-loop optimization system that gets smarter with every dollar spent.

Must Have:
Has built platform/tooling systems that unlock new capabilities for users, not just internal plumbing.

  • Strong TypeScript or Python with fast production shipping ability.

  • Experience with browser automation, screen capture, simulation, or experimentation infrastructure.

  • Strong product instincts for turning messy data and workflows into usable tools.

  • AI-first development workflow with high implementation velocity.

Nice to have:
Simulation engine / Monte Carlo / probabilistic modeling experience

  • Computer vision or image analysis (for creative intelligence)

  • Ad-tech or growth engineering background

  • A/B testing or experimentation infrastructure experience

  • Experience with Mastra, Langchain, or LLM orchestration frameworks

Own the platform and simulation layer of Learn Engine. Build the campaign simulator, experimentation infrastructure, screen-capture and creative-intelligence pipelines, and client-facing data products that let operators model outcomes before spending real money. This role owns tooling, infrastructure, simulation fidelity, and productized research surfaces — not the optimization policy itself.

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