we are looking for a Software Engineer – Verification and Reliability.
In this role as a SDET (Software Development Engineer in Test), you are a developer first. You will join a high-impact team of engineers who write production-grade code to build a massive-scale validation ecosystem. Your job is to act as "The Breaker"-designing the infrastructure, chaos experiments, and AI-driven tools that push our platform to its theoretical limits.
What Youll Build:
Adversarial Engineering: Design and implement Python-based distributed frameworks capable of orchestrating millions of concurrent IO operations to hunt down race conditions and memory leaks.
AI-Augmented Validation: Be at the forefront of the AI-Native transformation. You will leverage LLMs and Generative AI to automate complex scenario generation, build intelligent agents for root-cause analysis, and multiply your engineering velocity.
Simulation & Chaos: Build the "Entropy Engine." You will develop tools that inject real-world failures – latency, packet loss, and hardware crashes – to prove the resilience of our Raft and RDMA implementations.
Deep-System Observability: Move beyond "Pass/Fail." You will build telemetry pipelines to track P99 latency and jitter, providing critical architectural feedback to the Core Kernel teams.
Collaborative Architecture: You will operate with the same rigorous standards as the Core R&D team: design docs, production-grade code reviews, and high-level architectural planning.
In this role as a SDET (Software Development Engineer in Test), you are a developer first. You will join a high-impact team of engineers who write production-grade code to build a massive-scale validation ecosystem. Your job is to act as "The Breaker"-designing the infrastructure, chaos experiments, and AI-driven tools that push our platform to its theoretical limits.
What Youll Build:
Adversarial Engineering: Design and implement Python-based distributed frameworks capable of orchestrating millions of concurrent IO operations to hunt down race conditions and memory leaks.
AI-Augmented Validation: Be at the forefront of the AI-Native transformation. You will leverage LLMs and Generative AI to automate complex scenario generation, build intelligent agents for root-cause analysis, and multiply your engineering velocity.
Simulation & Chaos: Build the "Entropy Engine." You will develop tools that inject real-world failures – latency, packet loss, and hardware crashes – to prove the resilience of our Raft and RDMA implementations.
Deep-System Observability: Move beyond "Pass/Fail." You will build telemetry pipelines to track P99 latency and jitter, providing critical architectural feedback to the Core Kernel teams.
Collaborative Architecture: You will operate with the same rigorous standards as the Core R&D team: design docs, production-grade code reviews, and high-level architectural planning.
Requirements:
Extensive Coding Experience: 5+ years of hands-on Python development experience is required. You are a Python expert who understands the language "under the hood" and are comfortable reading and debugging C++, Rust, or Go to understand how the core system works.
Systems Engineering Mindset: You have a background in distributed systems, networking (TCP/IP, RDMA), or storage protocols. You understand the complexities of consistency and metadata at scale.
AI Enthusiast: You are an early adopter of AI tools (Copilot, LLMs) and are excited about using them to automate the most tedious parts of the engineering lifecycle.
The "SRE" Lens: You approach quality through the lens of Site Reliability Engineering. You care about observability, MTTD (Mean Time to Detection), and building self-healing testing loops.
Problem Hunter: You have a "hacker" instinct. You dont just find a bug; you find the architectural flaw that allowed it to exist.
Extensive Coding Experience: 5+ years of hands-on Python development experience is required. You are a Python expert who understands the language "under the hood" and are comfortable reading and debugging C++, Rust, or Go to understand how the core system works.
Systems Engineering Mindset: You have a background in distributed systems, networking (TCP/IP, RDMA), or storage protocols. You understand the complexities of consistency and metadata at scale.
AI Enthusiast: You are an early adopter of AI tools (Copilot, LLMs) and are excited about using them to automate the most tedious parts of the engineering lifecycle.
The "SRE" Lens: You approach quality through the lens of Site Reliability Engineering. You care about observability, MTTD (Mean Time to Detection), and building self-healing testing loops.
Problem Hunter: You have a "hacker" instinct. You dont just find a bug; you find the architectural flaw that allowed it to exist.
This position is open to all candidates.
