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We are seeking a talented and experienced Software Engineer to design, build, and optimize high-performance distributed systems, core data engines, and backend infrastructure. This role requires deep system-level architecture understanding, the ability to handle large-scale clusters processing petabytes of data, and mastery of modern C/C++ and Linux environment internals.
What You'll Do:
Design and develop core components of a next-generation distributed event-streaming and messaging platform.
Implement and maintain a high-scale, high-performance Kafka-protocol-compatible broker.
Build scalable and resilient distributed services handling petabytes of data across large clusters.
Design solutions around correctness semantics (ordering guarantees, transactions, exactly-once / idempotence, repartitioning), load balancing, replication, fault tolerance, and scalability
Investigate and resolve complex production issues across the full produce-to-consume path - from the Kafka client that produced it, through the broker and all the layers in between, all the way to the consumer.
Collaborate closely with architects, researchers, and engineering teams to deliver high-performance data infrastructure powering AI, analytics, and enterprise workloads.

Most QA roles are about writing scripts to catch bugs after the code is written. This isn't one of those roles.
At our company, we aren't just scaling software; we are building the fundamental engine that powers the global AI revolution. When you are managing exabytes of data at breaking-point speeds, traditional testing methodologies crumble. We don't need someone to follow a test plan. We need an architect to build a self-evolving, intelligent testing ecosystem.
The Mission
We want you to build the AI tools that validate our AI data platform. You will design autonomous, agentic systems that actively look for vulnerabilities, orchestrate their own testing logic, navigate distributed dependencies, and isolate regressions entirely on their own before they hit production.
If you are a systems-level builder who gets excited by complex distributed systems, autonomous logic, and breaking things at an elite engineering scale, this is your playground.
What Youll Actually Do Everyday
Build AI Agents for Quality: Design and deploy production-grade Python frameworks and LLM-driven agentic tools that dynamically generate, execute, and self-correct test environments.
Orchestrate Chaos at Scale: Move past static assertions. Youll build runtime verification tools that stress-test data integrity, multi-node failures, and deep storage engine behaviors.
Ditch the Manual Mindset: Drive our entire automation architecture toward a state where human intervention is the exception, not the rule.
Partner with Core R&D: Work side-by-side with our systems architects to inject intelligent code evaluation pipelines right into our fast-moving CI/CD engines.