About the role
At Imterix, we engineer AI, robotics, cloud, and cybersecurity platforms that operate inside mission-critical enterprise environments where technical failure has real consequences. As a Data Platform Engineer, you will architect, scale, and maintain the high-throughput streaming and storage infrastructure that powers our foundational AI models, autonomous robotics fleets, and real-time security systems. You will build software engineered to withstand continuous production stress—not just perform in controlled demo environments.
What you will do
- Architect Enterprise Data Pipelines: Design, deploy, and scale batch and real-time data streaming pipelines capable of processing terabytes of sensor telemetry, financial transactions, and cybersecurity audit logs.
- Support MLOps & Retrieval Pipelines: Partner with AI researchers to build scalable feature stores, vector search indexes, and dataset management tools for foundation model fine-tuning and retrieval-augmented workflows.
- Ensure High Availability & Low Latency: Optimize distributed storage and query engines to meet strict SLAs across high-stakes sectors like healthcare, finance, logistics, and manufacturing.
- Enforce Security & Data Governance: Implement fine-grained access controls (RBAC), end-to-end data encryption, and automated audit logging to satisfy strict enterprise compliance requirements.
- Build Production Observability: Implement automated monitoring, schema validation, and self-healing alerts to prevent data drift, corruption, or pipeline failures under heavy operational loads.
What we are looking for
- 4+ years of professional engineering experience building high-throughput data platforms or distributed backend infrastructure.
- Proven track record of operating mission-critical data systems in continuous production environments.
- Deep knowledge of distributed systems, query optimization, data modeling, and schema evolution strategies.
- Solid understanding of DevOps principles, containerization, and infrastructure as code.
- Experience handling high-frequency telemetry from robotics, industrial IoT, or hardware systems.
- Hands-on background with MLOps frameworks, feature stores (Feast), or LLM evaluation infrastructure.
- Knowledge of zero-trust architecture or high-volume cybersecurity event processing.
Applications close: 3 September 2026