Senior Software Engineer, Infrastructure & Platform (Full-Stack)

AfterQuery is a research lab investigating the boundaries and capabilities of artificial intelligence through novel datasets and experimentation. Their customers are the frontier AI labs; every major foundation model lab is a client. Backed by Y Combinator, BoxGroup, ex-partners from Lightspeed and Index Ventures, and senior leadership at Google DeepMind and Meta GenAI, AfterQuery was one of the fastest-growing YC companies in their batch.

The founding team brings backgrounds from Jane Street, Meta, Citadel Securities, Google, Goldman Sachs, Morgan Stanley, Silver Lake, Berkeley AI Research (BAIR), and Stanford AI Lab (SAIL).

About the Role

As a Senior Software Engineer, Infrastructure and Platform at AfterQuery, you will design and build the core infrastructure that powers their data generation, evaluation, and agentic systems. You will be responsible for the shared platforms that enable 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.

Key Responsibilities

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

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

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

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

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

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

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

Requirements

Must-Have

• 5+ years of 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, or equivalent)

• 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 at scale

• Background at a top-tier startup or FAANG-equivalent, this is a strong signal of fit

Nice-to-Have

• 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