Senior Software Engineer - Infrastructure & Platform

AfterQuery

$130K — $180K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of experience in production distributed systems or platform infrastructure
  • Proficiency in backend technologies like Python or JavaScript (Node.js / Next.js)
  • Experience with cloud environments, especially GCP or AWS
  • Familiarity with message queues and event-driven architectures
  • Background in high-throughput data pipelines and asynchronous systems
  • Strong grasp of system scalability, performance, and reliability metrics
  • Prior ownership of systems in production environments

Responsibilities

  • Design and build core infrastructure systems
  • Develop scalable distributed systems for large datasets
  • Build internal platforms and reusable APIs for engineering teams
  • Optimize performance, reliability, and observability of systems
  • Own the architecture for data pipelines and compute infrastructure
  • Collaborate with engineers and researchers for AI experimentation
  • Establish best practices for systems design and operations

Benefits

  • Opportunity to work closely with the founding team
  • Ownership of impactful infrastructure projects
  • Focus on cutting-edge technologies and AI systems
  • Engagement with multiple teams for cross-functional collaboration
  • Support for professional growth and engineering best practices
Full Job Description
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.

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

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