Lead technical decision-making and custom development for core infrastructure components, extending from foundational storage to high-availability service layers.
Deep-dive into performance tuning and systems internals—such as state management, checkpointing, and exactly-once semantics—to ensure millisecond-level accuracy at global scale.
Develop and integrate the Knowledge Platform, enabling AI-driven products through scalable vector indexing, agentic workflows, and real-time data streaming.
Own the full SDLC for high-performance distributed systems (batch and streaming) that process petabytes of data across 30+ global regions.
Advocate for elite software engineering practices, contributing to shared tooling, SDKs, and automation frameworks that enhance the productivity of engineering teams company-wide.
Act as a technical beacon and mentor for mid-level engineers, driving project delivery through design reviews and technical leadership.

Have 5+ years of experience building and operating large-scale distributed systems or infrastructure platforms.
Possess a deep understanding of computer science fundamentals, including distributed systems, memory management, and networking protocols.
Are proficient in Java, Kotlin, or Go.
Have hands-on experience (or the desire to deep-dive) into the internals of Kafka, Flink, Spark, Kubernetes, or OLAP engines.
Have a proven track record of taking 0-1 ownership of complex technical challenges, from initial design to production stability.
Are intrinsically motivated to explore emerging tech in AI/ML infrastructure and real-time systems to create tangible business impact.

Senior Software Engineer, Data Platform – AI Enablement

Key skills