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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.
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
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