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Job Title: Founding Production Systems Engineer
Location | On-Site — San Francisco, CA
Time Zone | PST

Role Overview:
We are seeking a Founding Production Systems Engineer to join an early-stage AI video infrastructure startup. The company's first product turns prompts and documents into whiteboard-style explainer videos in seconds, working toward a bigger vision of making video generation as fast, cheap, and programmable as text is today. As one of the first engineering hires, you will keep the product's core systems reliable and scalable as usage grows — debugging ambiguous production issues, improving observability, and making sure the system runs smoothly and cost-effectively over time.

Key Responsibilities:
- Improve reliability of job execution, queueing behavior, and failure recovery
- Build monitoring, alerting, and incident-response workflows suited for an early but serious production system
- Design systems that scale expensive workflows without hurting speed or predictability
- Improve cost efficiency across compute, storage, and third-party services
- Build internal tools that simplify debugging and system operations for the team
- Partner with the broader team to align product needs with robust technical solutions

Required Qualifications:
- Experience operating production infrastructure or high-throughput backend systems
- Strong debugging skills across services, networking, storage, and cloud environments
- Familiarity with queues, object storage, databases, and observability tooling
- Comfortable owning ambiguous reliability problems without a predefined root cause
- Practical judgment about when to automate, simplify, or build minimal robust solutions
-Comfortable using AI tools to increase speed, while relying on personal judgment to solve problems
- Must be willing to work on-site in San Francisco, CA

Preferred Qualifications:
- Experience clearly communicating tradeoffs to non-infrastructure engineers
- Track record of owning outcomes independently, not just executing tickets
- Comfortable making infrastructure decisions with limited oversight

Tools & Technology:
- Queueing systems and object storage
- Databases and observability tooling
- Cloud infrastructure and deployment automation
- AI-assisted development tools

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