Senior Data Engineer - AI Infrastructure

Payward is the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks. Kraken, founded in 2011, is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions globally. The AI Infrastructure team builds and operates production systems powering intelligent agents at scale, focusing on model inference, orchestration, and execution layers.

• 5+ years in data engineering with at least 2 years focused on streaming systems in production
• Hands-on experience with RisingWave, Apache Flink, Kafka Streams, or comparable stream processing frameworks
• Strong understanding of feature store design including online/offline consistency, point-in-time correctness, and low-latency serving
• Experience building data pipelines feeding production ML models or inference systems
• Proficiency in Python and/or Scala; SQL fluency required
• Familiarity with data quality frameworks, pipeline observability, and SLA ownership
• Comfortable operating in a fast-moving, ambiguous environment within an AI-focused team

Nice to haves:

• Direct experience with RisingWave in production
• Exposure to inference pipeline architecture or model serving infrastructure
• Experience with feature platforms
• Crypto or fintech domain experience

• Own and evolve streaming data pipelines powering live inference and real-time model serving
• Design and build feature stores serving low-latency, high-reliability features to production ML models
• Implement and maintain streaming systems using RisingWave, Apache Flink, or Kafka Streams
• Partner with ML engineers and AI infrastructure teams to define data contracts, feature schemas, and pipeline SLAs
• Drive pipelines toward real-time processing, reducing latency from hours to seconds
• Ensure data quality, observability, and auditability across streaming and feature engineering systems
• Contribute to inference pipeline tooling where data engineering and model serving intersect
• Evaluate emerging streaming and feature store technologies and shape the team's technical roadmap

Applicants may redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. The employer considers qualified applicants with criminal histories consistent with the San Francisco Fair Chance Ordinance. The employer is an equal opportunity employer and does not tolerate discrimination or harassment based on protected characteristics as outlined by law.