--- title: 'Principal Data Engineer at readyon.ai' canonical: 'https://feeny.ai/job/principal-data-engineer-readyon-ai-san-francisco-dp1jx9p7d1be' type: 'job' last_seen: '2026-09-05' --- # Principal Data Engineer at readyon.ai - **Company:** readyon.ai - **Location:** San Francisco, CA - **Employment:** full-time - **Work type:** onsite - **Posted:** 2025-11-26 - **Last confirmed live:** 2026-09-05 - **Apply:** https://jobs.gem.com/careers-readyon/am9icG9zdDpp724mJiKKmKi3-7qwQbzG ## Job description Transform How Frontline Work Runs Enterprises struggle to manage hundreds of millions of dollars in frontline labor spend due to decades-old software and manual processes, creating massive, avoidable costs. Frontline labor often represents 40% of the P&L, yet the systems managing this $3 trillion market were built for static schedules and limited flexibility. ReadyOn was founded to reject that paradigm. Staffing is not a scheduling problem; it is a real-time supply–demand orchestration problem. ReadyOn is an AI-native labor operating system, built from the ground up for AI agents to perform real-time labor optimization - much like ridesharing platforms that match drivers and riders in real time, but applied to frontline labor instead of fixed, one-size-fits-all schedules. Who’s Building It AI is not a bolt-on feature in our platform. Every decision, from demand forecasting to shift assignment, flows through an adaptive, autonomous decision layer that learns from operational data and continuously optimizes for cost, compliance, and worker satisfaction. Behind that system is a founding team of experts in labor markets, enterprise software, and AI-enabled platforms: [Reza](https://www.linkedin.com/in/reza-iranmanesh-13462b30/) – Engineering leader who scaled enterprise systems at Google, Yahoo, and AT&T [Dominic](https://www.linkedin.com/in/dom-mirabile/) – Operator who optimized labor-intensive operations in 21 countries [Mohammad](https://www.linkedin.com/in/mohammad-akbarpour-46773127/)– Stanford professor and leading expert in algorithmic market design ReadyOn has already proven product–market fit with multiple multi-million-dollar customers, consistent expansion within existing accounts, and measurable ROI that moves stock prices. Hands-On Builders Leading AI Innovation We’re building a top-tier engineering team to reimagine how labor is managed at scale. As a Principal Data Engineer, you will own the data platform and core data services that power ReadyOn’s real-time labor operating system, enabling AI agents to orchestrate frontline work across thousands of shifts, locations, and workers every day. Ideal candidates - Are hands-on senior engineers who thrive in ambiguous, high-impact environments and naturally set technical direction for others.​ - Care deeply about clean system design, scalability, and elegant architecture across both data and backend systems, and are not afraid to rethink default patterns.​ - Enjoy working closely with product, design, and AI research teams to deliver new data-driven experiences customers actually use.​ - Focus on business outcomes, not just technical output, and love solving real business problems with data, services, and automation.​ ## Responsibilities - Design, build, and scale data pipelines and data services using Python, TypeScript, Apache Airflow, PySpark, AWS Glue, and Snowflake to support both real-time and batch workloads.​ - Design, operationalize, and monitor ingest and transformation workflows, including DAGs, alerting, retries, SLAs, and robust data quality checks for production environments.​ - Collaborate with AI, platform, and backend teams to automate ingestion, data validation, and real-time compute workflows, and drive the roadmap toward a production-grade feature store that supports AI agents and decisioning.​ - Partner closely with the core engineering team to shape ReadyOn’s Integration Platform, ensuring external systems (HCM, WFM, payroll, timekeeping, and other enterprise tools) integrate cleanly and are observable end to end in ReadyOn dashboards.​ - Model data structures and implement efficient, scalable transformations in Snowflake and PostgreSQL, including schema design, indexing, partitioning, and query optimization for high-volume, low-latency use cases.​ - Build reusable frameworks, connectors, and internal libraries that standardize how data is published, discovered, and consumed by backend services, analytics, and AI workloads.​ - Implement and continuously improve observability across pipelines and services: structured logging, metrics, tracing, data quality monitoring, lineage, and incident response playbooks.​ - Provide technical leadership on data and backend integration: participate in system design and code reviews, mentor other engineers, and help drive sound, pragmatic technical decisions in a fast-moving environment.​ ## Your background - 5 plus years of production data engineering experience, including owning critical pipelines, datasets, and services in live environments.​ - Deep, hands-on experience with Apache Airflow, AWS Glue, PySpark, and Python-based data pipelines, including orchestration, monitoring, and troubleshooting at scale.​ - Solid SQL skills and experience working with PostgreSQL in production: schema design, query optimization, migration management, and handling concurrency in large-scale environments.​ - Strong understanding of cloud-native data and service workflows (AWS preferred), including data warehousing, storage, security, and cost-efficient architectures.​ - Fluency in TypeScript and experience with a backend framework such as NestJS (or other Node.js frameworks), including designing decoupled services and robust enterprise interfaces; GraphQL experience is a significant plus.​ - Experience implementing observability for data and backend systems: logging, metrics, tracing, data validation, and automated alerts for pipeline and service health.​ - Comfortable collaborating with AI/ML and data science teams, understanding how data flows into models, feature stores, and real-time decisioning workflows, even if you are not a data scientist yourself.​ - Bonus: hands-on experience with conflict resolution in collaborative or concurrent-editing systems, graph processing, feature stores, or real-time coordination tools and algorithms.​ If you’re looking for predictability, rigid structure, or narrow specialization, this probably isn’t the right role. This is a principal-level position for hands-on builders who want to define the data foundation of an AI-native labor operating system and shape how data, AI, and backend services come together in production. Interview Process - Screening call with Talent (Recruiter) - 1:1 interview with Founder/CTO, Reza Iranmanesh (hiring manager) - Technical panel: cross-functional technical interview (virtual) - Onsite interview with direct team and select founding members Location: Why In-Person Matters As a high-growth startup tackling complex, industry-defining challenges, in-person collaboration is essential to our success. Being together in our San Francisco office enables rapid decision-making, creative problem-solving, and strong team trust, critical in this formative phase. You’ll be required to work onsite, Monday through Friday, to help shape our culture, accelerate learning, and build the foundational technology that will define ReadyOn’s future. ## Compensation Final compensation will be determined based on your skills, experience, and geographic location. In addition to salary, this role may include comprehensive benefits, bonuses, commissions, and a meaningful equity stake in ReadyOn. Potential Recruitment Fraud Memo Recruiting at ReadyOn is handled directly by our in-house team or verified hiring partners. We will never request payment, bank details, or confidential personal information during our recruitment process. If you are contacted by someone claiming to represent ReadyOn and you are concerned about the legitimacy of the interaction, please contact us at careers@readyon.ai to verify any communication. ## EEO Statement ReadyOn is committed to building a diverse and inclusive workplace. We are proud to be an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. ## About readyon.ai ## Company Overview - **One-liner**: ReadyOn builds an AI-native labor operating system that continuously matches supply and demand for frontline workforce deployment. - **Entity Type**: Private (Series A) - **Headquarters**: San Francisco, California, United States - **Founded**: 2023 (conflicting reports list 2022; company site states 2023) [readyon.ai/about](https://www.readyon.ai/about) - **Founders**: Dominic Mirabile (CEO), Reza Iranmanesh (CTO), Mohammad Akbarpour (Chief Scientist) [readyon.ai/about](https://www.readyon.ai/about) ## Core Business - **Primary industry**: Enterprise Labor Technology / HR Tech - **Target customers**: B2B, Enterprise – specifically frontline enterprises in industries like retail, hospitality, healthcare, logistics, and manufacturing. - **Mission**: “We’re building the system that runs labor” – helping enterprises continuously and intelligently deploy the right workers to the right place at the right time. ## Products & Services - **ReadyOn Labor Operating System** (SaaS): An AI-driven platform that ingests labor signals from financial systems, HCM, demand planning, time & attendance, and contingent labor sources. It predicts labor needs, matches supply to demand continuously, and acts on exceptions in real time. The system automates shift creation, ranks workers by fit and availability, and provides managers with insights to reduce labor cost and improve schedule flexibility. [readyon.ai/about](https://www.readyon.ai/about) ## Market Standing - **Valuation/Market Cap**: Not publicly disclosed - **Key Metric**: Total funding raised – over $30M (Series A, announced on careers page) [readyon.ai/careers](https://www.readyon.ai/careers) - **Notable Investors/Partners**: Venrock, Floodgate, Cowboy Ventures, Construct Capital [readyon.ai/careers](https://www.readyon.ai/careers) - **Growth Signals**: 57 employees (as of late 2024/early 2025) with 222.7% year-over-year headcount growth; presence in 80+ global markets; partnerships with “market-leading and most admired frontline enterprises” [linkedin.com](https://linkedin.com/company/readyon-ai) [readyon.ai/about](https://www.readyon.ai/about) ## Competitive Advantages - **Deep academic foundation**: Co-founded by Stanford economist Mohammad Akbarpour, with Susan Athey (Stanford Professor) as Chief AI Architect and Nobel laureate Paul Milgrom as Advisor. The company’s core insight treats labor coordination as a continuous matching problem, not a static scheduling problem, giving it a unique intellectual moat. [readyon.ai/about](https://www.readyon.ai/about) - **AI-native design**: Built from the ground up to use AI models and agents for real-time, continuous labor matching, handling complex constraints and exceptions. - **Enterprise-grade infrastructure**: Reads signals from multiple enterprise systems (financial, HCM, time & attendance, etc.) and acts proactively, making it a system of action rather than a passive reporting tool. ## Strategic Focus - **Current priorities**: Expanding the platform’s ability to continuously match labor supply to demand across large, distributed frontline enterprises. Deepening integrations with existing enterprise systems and scaling AI capabilities to handle more complex labor signals. Growing headcount and market presence globally. [readyon.ai/about](https://www.readyon.ai/about) ## Why Work Here - **Culture & values**: Emphasizes humility, ownership, lifting others, and simplicity. The team is described as “senior, spun out of Stanford, startups, and big tech.” [readyon.ai/careers](https://www.readyon.ai/careers) - **Work model**: The San Francisco headquarters is onsite, but the workforce is distributed across 8 countries (U.S., Pakistan, Brazil, Finland, Bolivia, U.K., Philippines, Mexico), suggesting a hybrid or remote-friendly environment for certain roles. [linkedin.com](https://linkedin.com/company/readyon-ai) - **Impact**: Described as “one of the highest-impact problems in the enterprise” and “one of the most consequential real-world applications of AI.” Employees are told they will “take real ownership” and build systems that matter in the real economy. [readyon.ai/about](https://www.readyon.ai/about) - **Engineering culture**: 55% of employees are in technical roles; the team is senior-heavy (27% senior, 10% manager). Notable alumni from Stanford, top tech companies, and startups. [linkedin.com](https://linkedin.com/company/readyon-ai) ## Sources 1. [readyon.ai/careers](https://www.readyon.ai/careers) 2. [readyon.ai/about](https://www.readyon.ai/about) 3. [linkedin.com](https://linkedin.com/company/readyon-ai) 4. 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