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
Overview
As a Software Engineer - Platform Infrastructure 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
Architect and develop the shared infrastructure powering our 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.
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
