This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer – Agents Systems based in Canada. This role sits at the core of a fast-evolving AI engineering function focused on building internal agent systems that dramatically improve execution speed across the organization. You will design and scale real-time data infrastructure powering AI-driven workflows, inference systems, and internal automation tools. The environment blends applied AI, backend engineering, and high-performance data systems, where experimentation and production-grade reliability go hand in hand. You will work closely with ML engineers, infrastructure teams, and product stakeholders to build streaming pipelines and feature systems that directly impact decision-making and system intelligence. This is a high-impact role where your work will shape how data is transformed into real-time, actionable intelligence. The team operates in a fast-paced, highly technical setting with strong emphasis on ownership, iteration, and system-level thinking. \n

Accountabilities: Design, build, and maintain real-time streaming data pipelines supporting AI and inference systems Develop and optimize low-latency feature stores ensuring consistency across online and offline environments Implement streaming architectures using tools such as Kafka Streams, Apache Flink, or RisingWave Collaborate with ML engineers to define data contracts, feature definitions, and pipeline SLAs Improve latency by migrating batch-based systems toward real-time streaming architectures Ensure observability, reliability, and data quality across all pipelines and feature systems Support inference and agent system workflows where data engineering and ML serving intersect Evaluate and integrate new streaming and feature engineering technologies to evolve the platform Requirements 5+ years of experience in data engineering, including at least 2+ years working with streaming systems in production Hands-on experience with Kafka Streams, Apache Flink, RisingWave, or similar frameworks Strong knowledge of feature store design, including real-time serving and point-in-time correctness Experience building pipelines that support production ML models or inference systems Proficiency in Python and/or Scala, with strong SQL skills Experience with data observability, monitoring, and pipeline reliability best practices Ability to work in fast-paced, ambiguous environments within AI-driven engineering teams Strong collaboration skills when working with ML, infra, and product stakeholders Experience with distributed systems and scalable backend architectures Benefits Competitive compensation aligned with senior-level data engineering roles Fully remote-friendly or hybrid flexibility (depending on team setup) Comprehensive health, dental, and vision coverage Retirement savings plan and long-term incentive opportunities Paid time off and flexible vacation policy Exposure to cutting-edge AI agent systems and real-time data infrastructure Learning and development support in advanced data and AI technologies Collaborative, high-ownership engineering culture focused on impact

\n How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1