WEKA is architecting a new approach to the enterprise data stack built for the age of reasoning.
NeuralMesh by WEKA sets the standard for agentic AI data infrastructure with a cloud and AI-native software solution that can be deployed anywhere. It transforms legacy data silos into data pipelines that dramatically increase GPU utilization and make AI model training and inference, machine learning, and other compute-intensive workloads run faster, work more efficiently, and consume less energy.
WEKA is a pre-IPO, growth-stage company on a hyper-growth trajectory. We help the world’s largest and most innovative enterprises and research organizations, including 12 of the Fortune 50, achieve discoveries, insights, and business outcomes faster and more sustainably. We’re passionate about solving our customers’ most complex data challenges to accelerate intelligent innovation and business value. If you share our passion, we invite you to join us on this exciting journey.
The Mission At WEKA, we are building NeuralMesh™- the world’s first intelligent, adaptive mesh storage system. To ensure our platform is unbreakable for the world’s largest AI and GPU clusters, we don't just "test" our code. We build an
adversarial distributed system as complex and sophisticated as the product itself.
We are moving away from traditional QA automation. We are building a high-octane engineering force that treats reliability as a high-end software problem. We need "Quality Hackers" who want to build the technology that proves bugs don't exist.
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 You’ll 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: You are a Python expert who understands "under the hood" internals. You 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 don’t just find a bug; you find the architectural flaw that allowed it to exist.
Why Join This Group?
You will be part of a newly restructured group led by veteran systems architects, moving at the speed of a startup with the impact of a global leader. If you are a backend engineer who wants to solve the hardest problems in computer science—verifying correctness in a massive asynchronous system—this is your home.
