Proficiency in JavaScript (Next.js) and Python for full-stack development.
Experience with serverless architecture and cloud functions on GCP or AWS.
Hands-on with Redis and Elasticsearch for building scalable data pipelines.
Familiarity with message queues like Kafka or RabbitMQ is essential.
Background in AI research, LLM evaluation, or human-in-the-loop systems is a plus.
Experience in bringing ideas to production, particularly in a startup or founder role.
Responsibilities
Build and scale complex data capturing workflows across web and desktop.
Architect and optimize data pipelines for high throughput and heavy loads.
Collaborate with founders to define product strategy and deliver features quickly.
Set best engineering practices to support future team growth.
Own entire projects end-to-end, making a direct impact on development.
Benefits
Opportunity to own projects with direct impact.
Role in defining product strategy as an early hire.
High level of responsibility and autonomy in decision-making.
Potential for significant equity benefits over time.
Full Job Description
Overview
As one of our core engineers, you'll be critical in creating data infrastructure that will be shaping the future development of frontier models. You will be one of our first hires, and will get a lot of responsibility, owning entire projects end-to-end - meaning you can see your impact instantly.
Responsibilities
Build and scale complex data capturing workflows across web (Next.js) and desktop (Python)
Architect and optimize data pipelines that experience high throughput, with heavy loads
Collaborate with the founding team to define product strategy and ship features fast.
Set engineering best practices and lay the groundwork for future team growth.
Required Qualifications
Proficiency in JavaScript (Next.js) and Python, with demonstrated experience building full-stack web applications
Experience with serverless architecture and cloud functions for implementing heavy data processing (GCP/AWS)
Storage, caching & search: Hands-on with Redis (caching), Elasticsearch (indexing), and message queues (Kafka/RabbitMQ) to build scalable, low-latency pipelines.
Experience getting your ideas into production (founder experience preferred)
Preferred Qualifications
Background in AI research, LLM evaluations, or human-in-the-loop systems
