Senior AI Infrastructure Engineer

AfterQuery; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

AfterQuery is seeking a Senior Software Engineer - Infrastructure in San Francisco to design and build core infrastructure for data generation, evaluation, and AI workflows. You will own systems powering large-scale experiments and ensure they are scalable and reliable.

You will collaborate with the founding team to set architecture, establish engineering standards, and develop platforms that support high-throughput workloads, observability, and robust data pipelines for frontier AI models.

Qualifications

• Extensive experience building production distributed systems.
• Strong Python and/or JavaScript (Node.js/Next.js) skills.
• Experience designing/operating systems in cloud environments (GCP/AWS).
• Familiar with messaging systems (Kafka, RabbitMQ, Pub/Sub).
• Experience with high-throughput data pipelines and asynchronous processing.
• Proven ownership of production systems.

Responsibilities

• Architect and develop shared infrastructure powering data generation platforms.
• Build scalable systems with high-throughput workloads and reliability.
• Create reusable APIs for product engineers and researchers.
• Design observability, monitoring, and fault tolerance for production.
• Define long-term data pipelines, compute, orchestration, and storage.
• Collaborate with researchers to enable AI experimentation workflows.
• Set standards for system design, deployment, and operations.

Skills

Distributed systems

Python

JavaScript (Node.js/Next.js)

Cloud platforms (GCP/AWS)

Data pipelines

Observability & monitoring

Production ownership

Tools

Kafka

RabbitMQ

Pub/Sub

Job description

AfterQuery is seeking a Senior Software Engineer - Infrastructure in San Francisco to design and build core infrastructure for data generation, evaluation, and AI workflows. You will own systems powering large-scale experiments and ensure they are scalable and reliable.

You will collaborate with the founding team to set architecture, establish engineering standards, and develop platforms that support high-throughput workloads, observability, and robust data pipelines for frontier AI models.