Senior Software Engineer, Infrastructure & Platform

Role Overview

As a Senior Software Engineer, Infrastructure & Platform at AfterQuery, you will design and build the core infrastructure that powers our data generation, evaluation, and agentic systems.

You will be responsible for the shared platforms that enable our engineers and research teams to run large-scale human-in-the-loop workflows, evaluation harnesses, and automated data pipelines used to train frontier AI models.

This is a highly technical role with broad ownership. You will architect and build foundational infrastructure that many other engineers depend on, ensuring systems are scalable, reliable, and capable of supporting extremely high-throughput workloads.

You will work directly with the founding team to define system architecture, establish engineering best practices, and build the infrastructure that supports the next generation of AI development.

Company Overview

AfterQuery is a research lab investigating the boundaries and capabilities of artificial intelligence through novel datasets and experimentation. Our customers are the foundation model labs, and we serve all of the frontier AI labs.

We are based in San Francisco, CA, and have raised funding from top investors, including Y Combinator and BoxGroup, ex-partners from Lightspeed and Index Ventures, and senior leadership at Google DeepMind and Meta GenAI.

Our founding team brings backgrounds from Jane Street, Meta, Citadel Securities, Google, Goldman Sachs, Morgan Stanley, Silver Lake, Berkeley Artificial Intelligence Research (BAIR), and Stanford Artificial Intelligence Laboratory (SAIL).

Why Apply

Massive Opportunity:
We were one of the fastest-growing YC companies in our batch, and we believe we can become one of the fastest-growing YC companies of all time.

Founding Impact:
You will own and architect core infrastructure systems that power our platform from the ground up.

Equity & Growth:
Competitive salary and meaningful equity. As we scale, you’ll have the opportunity to shape the engineering organization and lead major technical initiatives.

Strong Team:
Our founding team has experience from Citadel Securities, Meta, Google, Silver Lake, and Morgan Stanley — work alongside world-class engineers and researchers.

Responsibilities

Design and build core infrastructure systems

• Architect and develop the shared infrastructure powering our data generation platforms, human-in-the-loop systems, and evaluation pipelines.
  

Develop scalable distributed systems

• Build systems capable of processing large-scale datasets and high-throughput workloads with strong reliability guarantees.
  

Build internal platforms and shared services

• Create reusable infrastructure and APIs that enable product engineers and researchers to build quickly and reliably on top of core systems.
  

Optimize performance and reliability

• Design systems with strong observability, monitoring, and fault tolerance to support production workloads at scale.
  

Own infrastructure architecture

• Help define long-term system architecture across data pipelines, compute infrastructure, task orchestration, and storage systems.
  

Collaborate across engineering and research

• Work closely with engineers and researchers to support new AI experimentation workflows and platform capabilities.
  

Establish engineering best practices

• Define standards for system design, deployment, reliability, and infrastructure operations.
  

Required Qualifications

• Strong experience building production distributed systems or platform infrastructure
  

• Proficiency in Python and/or JavaScript (Node.js / Next.js) or similar backend technologies
  

• Experience designing and operating systems in cloud environments (GCP or AWS)
  

• Experience with message queues and event-driven systems (Kafka, RabbitMQ, Pub/Sub, etc.)
  

• Experience working with high-throughput data pipelines and asynchronous processing systems
  

• Strong understanding of system scalability, performance, and reliability
  

• Experience owning systems running in production environments
  

Preferred Qualifications

• Experience building internal developer platforms or shared infrastructure
  

• Experience supporting large-scale data processing pipelines
  

• Experience with AI infrastructure, LLM evaluation systems, or ML pipelines
  

• Experience working at high-growth startups or scaling early infrastructure
  

• Experience designing human-in-the-loop or workflow orchestration systems