Senior/Staff Data Platform Engineer (AI)

TL;DR

Senior/Staff Data Platform Engineer (AI): Designing and operating large-scale batch and streaming data pipelines to power AI training, analytics, and product features with an accent on event-driven architectures and data orchestration. Focus on building self-serve data platforms, ensuring data correctness at scale, and optimizing developer experience for data infrastructure.

Location: San Francisco, New York City, or Palo Alto. International candidates may be considered as the company provides region-tailored benefits.

Salary: $220K – $405K

Company

hirify.global is an AI-powered search and discovery engine building the future of information retrieval.

What you will do

• Design and operate large-scale batch and streaming pipelines for AI training, evaluation, and product features.
• Build event-driven systems using Kafka, Kinesis, or PubSub for real-time ingestion and transformation.
• Architect data orchestration using Airflow or Dagster, owning scheduling, SLAs, and observability.
• Establish guarantees for data correctness, freshness, and lineage to support rapid AI workload growth.
• Develop self-serve platforms that allow engineers and data scientists to operate their own pipelines.
• Mentor engineers and drive the long-term technical direction of the data ecosystem.

Requirements

• 5+ years (Senior) or 8+ years (Staff) of software engineering experience.
• Strong experience building production data infrastructure systems at scale.
• Proficiency in Python and at least one additional backend language (Go, TypeScript, etc.).
• Deep familiarity with data orchestration systems like Airflow or Dagster.
• Experience supporting ML/AI workflows, training pipelines, or evaluation systems.
• Strong systems thinking regarding reliability, latency, cost, and complexity tradeoffs.

Culture & Benefits

• Comprehensive U.S. benefits including equity, health, dental, vision, and retirement.
• Tailored benefit programs for employees based outside the U.S.
• Opportunity to shape the architecture of a high-growth AI platform.
• A culture that treats internal data platforms as products to improve developer experience.