About ReadyOn

ReadyOn is building the next generation of enterprise software to power complex, high-scale workforce operations for mega enterprises. Most of these companies still rely on decades-old systems designed for a slower, more predictable world—tools that can’t adapt to the real-time demands of modern business.

In contrast, our AI-native solution treats workforce management not as a scheduling exercise, but as a continuous supply-and-demand matching problem. Combined with a graph data architecture, our labor operating system is making the leap to the next generation of software; similar to the transition from taxi dispatch to ridesharing, but on a wider and larger scale.

There are many challenges to harmonize operations between humans and their many agent counterparts, including graceful concurrency controls, real-time collaboration, and draft, replay, and rebase functionalities… all at the data level and in a fully deployed relational database. This is an incredible opportunity to invent the next generation of enterprise software.

The co-founders are experts in labor markets, enterprise software, and AI-enabled platforms:

Mohammad is a Stanford professor and the leading expert in algorithmic market design
Dominic optimized labor-intensive operations in 21 countries
Reza scaled enterprise-grade systems at Google, Yahoo, and AT&T

We’ve already proven product-market fit, signing multiple multi-million-dollar customers, driving consistent expansion within existing accounts, and delivering measurable ROI that moves stock prices.

About the role

We’re building a top-tier engineering team to reimagine how labor is managed at scale.

Ideal candidates:

Are hands-on engineers who thrive in ambiguous, high-impact environments
Care deeply about system design, scalability, and elegant architecture, and are not afraid to reinvent the future
Want to work closely with product, design, and AI researchers to bring novel experiences to life
Prioritize outcomes over output and love solving real business problems

What you'll do

Build, optimize, and scale data pipelines and infrastructure using Python, TypeScript, Apache Airflow, PySpark, AWS Glue, and Snowflake
Design, operationalize, and monitor ingest and transformation workflows, including DAGs, alerting, retries, and SLAs
Collaborate with platform and AI teams to automate ingestion, data validation, and real-time compute workflows; work toward building a feature store
Collaborate and pair with the core engineering team to shape ReadyOn’s Integration Platform, including integrating pipeline monitoring with ReadyOn dashboards for full visibility and observability
Model data structures and implement efficient, scalable transformations in Snowflake and PostgreSQL
Build reusable frameworks and connectors to standardize internal data publishing and consumption

Ideal Experience

4+ years of production data engineering experience
Deep, hands-on experience with Apache Airflow, AWS Glue, PySpark, and Python-based data pipelines
Solid SQL skills and experience working with PostgreSQL in live environments
Strong understanding of cloud-native data workflows (AWS preferred) and pipeline observability
Hands-on experience with a backend TypeScript framework such as NestJS is a huge plus

ReadyOn AI

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