דרושים » מחשבים ורשתות » Senior Network Engineer - AI Datacenter

We are seeking a skilled software engineer to join our NPU software stack development team. This role involves developing high-performance GPU programming frameworks, runtime systems, and libraries for AI/ML workloads. You will be responsible for implementing, optimizing, and maintaining GPU software stack components to support distributed AI training and inference.
Key Responsibilities
Identify bottlenecks, analysis and optimize in distributed NPU eco-system
Design and develop NPU memory management system
Design and develop optimized NPU development framework, execution path and debugging
Develop compatibility with AI frameworks (Triton, PyTorch, JAX)
Write high-quality, well-tested code with comprehensive documentation
Collaborate with other teams (Hardware, Network, QA, AI Framework Integration)
Participate in code reviews and technical design discussions.

our company's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to our companys needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
our company Cloud Storage provides a suite of services like the scalable our company Cloud Storage (GCS) for unstructured data, high-performance managed lustre for AI/HPC workloads, and the managed Network File System (NFS) service filestore. These offerings are fundamental to our companyCloud's infrastructure, serving as the backbone for storing and accessing the vast datasets required for training and deploying AI models. In the AI era, this storage portfolio is crucial for enabling innovation, supporting compute-intensive tasks, and driving significant value for our company Cloud customers. The performance, scalability, and flexibility of these storage solutions are key to unlocking the potential of AI.
our company Cloud accelerates every organizations ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage our companys cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to our company Cloud as their trusted partner to enable growth and solve their most critical business problems.
Responsibilities
Help us figure out a strong roadmap to make Cloud Storage the best for AI/ML workloads.
Lead a team of Engineers to design, develop, and deploy new storage enhancements. Provide technical guidance, mentorship, and code reviews.
Architect and design scalable, reliable, and performant systems that meet the needs of the growing AI/ML customer base. Make data-driven decisions to optimize system performance and efficiency.
Troubleshoot complex technical issues, analyze performance bottlenecks, and develop innovative solutions to address customer challenges.
Work closely with product managers, customer engineers, and other stakeholders to understand customer requirements and ensure that Cloud Storage meets their needs.

we are transforming how organizations build, run, and scale AI and accelerated compute workflows with NeuralMesh, our intelligent, adaptive mesh storage system. Unlike traditional data infrastructures, which become more fragile as compute environments grow and performance demands increase, NeuralMesh becomes faster, stronger, and more efficient as it scales - providing a flexible, adaptable foundation for enterprise and agentic AI innovation that maximizes GPU utilization, accelerates time to first token, and lowers the cost of innovation.
we are a growth-stage company backed by world-class venture capital investors and AI infrastructure industry leaders. Our technology, purpose-built for AI, has garnered over 140 patents and is trusted by more than 30% of Fortune 50 enterprises, as well as the worlds leading hyperscalers, neoclouds, and AI innovators. Our team is customer-obsessed and works accountably, boldly, and collaboratively to ensure customer success. If we sound like your kind of people, join us!
About the role
At our company, were building a next-generation platform for validating large-scale distributed systems. Our goal is to continuously ensure the correctness, performance, and resilience of the company Data Platform across every layer of the stack.
As a Senior Software Engineer, youll work hands-on on the systems and frameworks that test, stress, and validate complex distributed infrastructure under real-world conditions. Youll help design and build automated environments that simulate scale, concurrency, and failure scenarios, and youll contribute to evolving how we ensure reliability and correctness in modern infrastructure systems.
This role is ideal for engineers with a strong distributed systems background who enjoy deep technical problem-solving, working close to the system, and building tools that improve quality, stability, and confidence at scale.
What Youll Do
Design and implement core components of a distributed testing infrastructure and quality platform.
Build automated frameworks to validate functionality, performance, and resilience at scale.
Collaborate closely with infrastructure, storage, and platform teams to ensure quality is built into the development lifecycle.
Contribute to improving tooling, test coverage, and engineering best practices across the organization.

we are architecting a new approach to the enterprise data stack built for the age of reasoning. NeuralMesh by our company 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.
we are a pre-IPO, growth-stage company on a hyper-growth trajectory. Weve raised $375M in capital with dozens of world-class venture capital and strategic investors. We help the worlds largest and most innovative enterprises and research organizations, including 12 of the Fortune 50, achieve discoveries, insights, and business outcomes faster and more sustainably. Were 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.
As a Senior Software Engineer, youll:
You will be responsible for building the "brain" of our companys main product, which is a distributed file system -the layer that manages orchestration, metadata, cluster membership, and implements complex logic required to manage hundreds of thousands of nodes, for cluster scaling, automated failover, zero-downtime rolling upgrades and "self-healing" to detect and remediate hardware failures or network partitions.
Design, implement, unit test, and maintain services that coordinate and the cluster
Optimize Performance: Work with complex data structures like spanning trees or LSM-Trees, concurrency control mechanisms (MVCC) to improve speed and efficiency.
Collaborate closely with cross-functional teams to translate backend capabilities into real-world impact.

we are architecting a new approach to the enterprise data stack built for the age of reasoning. NeuralMesh by our company 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.
we are a pre-IPO, growth-stage company on a hyper-growth trajectory. Weve raised $375M in capital with dozens of world-class venture capital and strategic investors. We help the worlds largest and most innovative enterprises and research organizations, including 12 of the Fortune 50, achieve discoveries, insights, and business outcomes faster and more sustainably. Were 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.
What youll be doing:
As our new Senior Software Engineer, youll be joining the Platform group. This group of highly-experienced and detail-oriented engineers proudly owns the network stack, storage stack, task scheduling infrastructure and more.
As a Senior Software Engineer, youll:
Play an active role in creating jaw-dropping designs, writing impressively efficient code, and conducting collaborative code review;
Share fresh ideas and architectural guidance for our core areas of distributed computing, high-performance storage, and cloud computing; and
Challenge our benchmarks with performance testing around IO and storage throughput.

we are transforming how organizations build, run, and scale AI and accelerated compute workflows with NeuralMesh, our intelligent, adaptive mesh storage system. Unlike traditional data infrastructures, which become more fragile as compute environments grow and performance demands increase, NeuralMesh becomes faster, stronger, and more efficient as it scales, providing a flexible, adaptable foundation for enterprise and agentic AI innovation that maximizes GPU utilization, accelerates time to first token, and lowers the cost of innovation.
we are a growth-stage company backed by world-class venture capital investors and AI infrastructure industry leaders. Our technology, purpose-built for AI, has garnered over 140 patents and is trusted by more than 30% of Fortune 50 enterprises, as well as the worlds leading hyperscalers, neoclouds, and AI innovators. Our team is customer-obsessed and works accountably, boldly, and collaboratively to ensure their success. If we sound like your kind of people, join us!
About The Position
At our company, we dont just "test" software; we push the boundaries of high-performance distributed systems. We are looking for a Group Lead for System Quality Engineering-someone who views quality as a complex engineering challenge, not a checkbox.
You will lead a group of 20 world-class SW engineers and Team Leads. Your mission is to build the "adversarial" engineering force that ensures our platform remains resilient, performant, and unbreakable under the worlds most demanding data workloads. We want a leader who treats testing as a performance art and a systems science, likely coming from a background in Backend Engineering, SRE, or highly technical System Verification.
Key Responsibilities:
Architect the "Breaking" Strategy: Design the end-to-end strategy for validating a massive-scale distributed file system. This isn't just about coverage; it's about finding the architectural breaking points.
Lead a High-Caliber Engineering Group: Manage and mentor a team of "Quality Hackers." You will set the technical bar, promote a culture of engineering excellence, and move away from traditional "manual-first" mindsets.
Deep-Tech Collaboration: Work as a peer to the Product and Core Development leads. Youll influence the product roadmap by identifying systemic risks early in the design phase.
Evolve the Automation Ecosystem: Partner with Infrastructure teams to build sophisticated, automated test environments that simulate chaotic, real-world customer environments at scale.
Field-to-Core Feedback Loop: Bridge the gap between how our product is used in the field and how we stress-test it in the lab, ensuring our company excels in the most extreme AI and HPC use cases.
Data-Driven Reliability: Define and track high-signal metrics (System Recovery Time, Latency P99s under stress, Mean Time to Detection) to provide a transparent view of product health.

We are seeking an experienced Solutions Data Engineer who possess both technical depth and strong interpersonal skills to partner with internal and external teams to develop scalable, flexible, and cutting-edge solutions. Solutions Engineers collaborate with operations and business development to help craft solutions to meet customer business problems.
A Solutions Engineer works to balance various aspects of the project, from safety to design. Additionally, a Solutions Engineer researches advanced technology regarding best practices in the field and seek to find cost-effective solutions.
Job Description:
Were looking for a Solutions Engineer with deep experience in Big Data technologies, real-time data pipelines, and scalable infrastructure-someone whos been delivering critical systems under pressure, and knows what it takes to bring complex data architectures to life. This isnt just about checking boxes on tech stacks-its about solving real-world data problems, collaborating with smart people, and building robust, future-proof solutions.
In this role, youll partner closely with engineering, product, and customers to design and deliver high-impact systems that move, transform, and serve data at scale. Youll help customers architect pipelines that are not only performant and cost-efficient but also easy to operate and evolve.
We want someone whos comfortable switching hats between low-level debugging, high-level architecture, and communicating clearly with stakeholders of all technical levels.
Key Responsibilities:
Build distributed data pipelines using technologies like Kafka, Spark (batch & streaming), Python, Trino, Airflow, and S3-compatible data lakes-designed for scale, modularity, and seamless integration across real-time and batch workloads.
Design, deploy, and troubleshoot hybrid cloud/on-prem environments using Terraform, Docker, Kubernetes, and CI/CD automation tools.
Implement event-driven and serverless workflows with precise control over latency, throughput, and fault tolerance trade-offs.
Create technical guides, architecture docs, and demo pipelines to support onboarding, evangelize best practices, and accelerate adoption across engineering, product, and customer-facing teams.
Integrate data validation, observability tools, and governance directly into the pipeline lifecycle.
Own end-to-end platform lifecycle: ingestion → transformation → storage (Parquet/ORC on S3) → compute layer (Trino/Spark).
Benchmark and tune storage backends (S3/NFS/SMB) and compute layers for throughput, latency, and scalability using production datasets.
Work cross-functionally with R&D to push performance limits across interactive, streaming, and ML-ready analytics workloads.
Operate and debug object store-backed data lake infrastructure, enabling schema-on-read access, high-throughput ingestion, advanced searching strategies, and performance tuning for large-scale workloads.

We are looking for Senior Software Engineer to join the Cumulus Linux team! We present you with an opportunity to be part of the team that develops the Network Operating System that powers data centers that are accelerated, disaggregated and software-defined to meet the exploding growth in AI and high-performance computing. You'll be part of a software development team responsible for defining and implementing core platform services, as well as Reliability, Availability and Serviceability features for Cumulus Linux, the Debian-based operating system for our market-leading Ethernet switches.

What you'll be doing:

Design and develop software for Cumulus Linux operating system (OS) which runs on our portfolio of data center switches.

Work on bringing up Cumulus Linux on next generation our switches.

Develop and maintain software in Python, C and Shell for our OS.

Collaborate with product, architecture, and engineering teams to deliver features on Cumulus Linuxs roadmap.

Debug and resolve issues reported by test and customer-facing teams.

Work with open source software that is part of our OS and fix issues as and when they are raised.

Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our company's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.
In this role, you will work with system teams and the CPU Architecture team to develop an understanding of the CPU, SoC, performance metrics, benchmarks/measuring tools, and available optimization knobs. You will define methods and technologies to model CPU performance at different accuracy levels by supporting architectural explorations and decision-making. In addition, you will correlate performance projections with measured post-silicon data.
The ML, Systems, & Cloud AI (MSCA) organization at our company designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all our company services (Search, YouTube, etc.) and our company Cloud. Our end users, Cloud customers and the billions of people who use our company services around the world.
We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including our company Clouds Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.
Responsibilities
Design, develop, test, deploy, maintain, and improve Central Processing Unit (CPU) software modeling and other software tools.
Manage individual project priorities, deadlines, and deliverables.
Collaborate with hardware and software CPU architecture teams, SOC performance modeling team, and other company Software teams.

We are looking for a Senior AI Software Engineer to help build and evolve AI-powered cybersecurity products that protect customers at global scale. In this role, you will design and implement intelligent systems leveraging AI agents and large language models (LLMs), partnering across engineering, security, and product teams to deliver secure, reliable, and responsible solutions.
This role requires strong software engineering fundamentals, hands-on experience building AI-driven systems, and a passion for applying cutting-edge AI technologies to solve complex security challenges.
Why Join Us
Youll be part of the Office of the CTO of our company Security, working on innovative, high-impact security products powered by AI that shape the future of cybersecurity. We foster a collaborative and inclusive culture that values a growth mindset, technical excellence, and continuous innovation.
Responsibilities
Design, develop, and maintain cutting-edge AI technologies and products within the Office of the CTO, from early prototypes to production-grade systems.
Build and evolve AI agent-based architectures, including multi-agent workflows and tool-using agents.
Apply advanced LLM design patterns to improve accuracy, robustness, and safety of LLM-powered systems, including prompt engineering, flow engineering, Retrieval-Augmented Generation (RAG), self-review, ReAct, and guardrails.
Write high-quality, secure, and maintainable code primarily in Python, following modern software engineering best practices.
Collaborate with cross-functional teams, including product, research, and security, to define requirements and deliver end-to-end AI solutions.
Identify and resolve reliability, performance, and security issues in AI-enabled services.
Contribute to architecture and design reviews, ensuring solutions meet security, privacy, compliance, and responsible AI requirements.
Mentor other engineers and contribute to a culture of engineering excellence and continuous learning.