Senior Data Engineer - Agents Systems

Kraken

1d • $110,400 - $220,800

About The Position

The Agent Systems team is a 0→1 engineering group building internal AI-powered agents that interact directly with company systems. The mandate is to dramatically increase internal speed of execution through automation, intelligent inference, and workflow orchestration. This team operates at the intersection of AI, backend systems, and applied product engineering. The work is pragmatic and fast-moving — prototypes are expected, but the bar for production reliability remains high. Engineers on this team move fluidly between experimentation and shipping, building systems that reason over user interactions and take meaningful action across internal tools. You’ll work closely with cross-functional partners across product, infrastructure, and internal operations to deploy agent-driven capabilities that compound leverage across the organization.

Requirements

• 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 — online/offline consistency, point-in-time correctness, low-latency serving
• Experience building data pipelines that feed 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 embedded 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

Responsibilities

• Own and evolve streaming data pipelines that power live inference and real-time model serving across Kraken's AI infrastructure
• Design and build feature stores that serve low-latency, high-reliability features to production ML models
• Implement and maintain streaming systems using RisingWave, Apache Flink, or Kafka Streams, selecting the right tool for the workload
• Partner with ML engineers and AI infra teams to define data contracts, feature schemas, and pipeline SLAs
• Drive pipelines toward real-time where batch exists today reducing latency from hours to seconds
• Ensure data quality, observability, and auditability across all 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

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed