AI Platform Engineer
Applied Compute29 days ago
San Francisco, CA, USAMid Level
Base Salary
$190k - $310k/yr
Responsibilities
- Own the full stack of the AC2 application platform.
- Integrate platform capabilities such as memory, context, and auto-research into user experiences.
- Design interfaces for interacting with agents, including consoles, dashboards, resource-management views, and observability UIs.
- Build tools for subject matter experts to capture and communicate workflows.
- Develop the AC SDK for internal and customer-facing engineers building domain-specific agents and applications.
- Build agent sandboxing user experiences and deployment surfaces for operation across different environments.
- Collaborate with product research engineers and applied research engineers on platform capabilities and customer deployments.
Requirements
- Strong full-stack engineering skills and experience shipping production web applications.
- Deep familiarity with LLM-powered applications and agent architectures.
- Experience with real-time and asynchronous systems.
- Ability to rapidly build and iterate on polished, functional applications with high engineering craft.
- Creativity, openness to prototyping, and strong attention to user experience.
- Experience with reinforcement learning from human feedback or similar human-in-the-loop learning systems is a strong-candidate qualification.
- Previous founder or zero-to-one early-engineer experience is a strong-candidate qualification.
- Published work or open-source contributions in AI/ML systems are a strong-candidate qualification.
Benefits
- Full-time role based in San Francisco with work from the company’s Mission office.
- $190,000–$310,000 U.S. base salary range plus meaningful equity.
- 100% employer-paid health insurance coverage.
- Unlimited paid time off.
- Paid parental leave.
- Daily lunches and dinners.
- Transportation and relocation support.
- Retirement plans.
- Visa sponsorship.
Categories
About Applied Compute
Applied Compute builds Specific Intelligence for enterprises, unlocking the knowledge inside a company to train custom models and deploy an in-house agent workforce.