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
