דרושים » תוכנה » GPU Senior Software Engineer

we are looking for a Senior Software Engineer.
The group is a high-powered team responsible for implementing algorithms at scales of 100s of PBs. The team also manages the core filesystem components, including blocks and metadata management, snapshots, RAID logic, object-store tiering, unique cloud disaster recovery features, and more. And most importantly, they skillfully handle the most delicate part of the solution - our customers data.
As a Senior Software Engineer, youll:
Design and develop distributed file system components to support data management features such as snapshots, replication, tiering, and advanced data reduction algorithms;
Participate in the design, architecture, and implementation of next-generation storage architecture;
Assist in technically managing initial storage implementations including proofs-of-concept;
Diagnose bottlenecks and implement clean and performant solutions to achieve unbeatable performance;
Design algorithms and data structures to make sure customer data is safe and coherent across our solution in a wide variety of failure modes; and
Constantly revisit the architecture, algorithms, and methodologies to improve productivity, reliability, and maintainability.

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.
Key Responsibilities
Design & Develop Core Components: Build, maintain, and optimize highly scalable, resilient distributed services, storage engines, or data-processing pipelines written in C/C++.
System Architecture & Resilience: Drive architectural discussions and implementations around high availability, data consistency, replication mechanisms, fault tolerance, and multi-node concurrency.
Performance Optimization: Optimize hot execution paths, low-level data structures, memory management, and I/O subsystems to guarantee high throughput and minimal latency.
Complex Debugging & Troubleshooting: Investigate and resolve intricate production issues spanning the application layer, distributed networking protocols, file systems, and operating system kernels.
End-to-End Ownership: Take full technical ownership of critical features-from ambiguous requirements and system design through implementation, rollout, and observability in production environments.
Teams
Storage Platform: Focuses on building a next-generation distributed storage platform handling petabytes of data across large clusters specifically designed to power AI, enterprise, and analytics workloads. Handling everything that touches the hardware and operating system aspects in a software defined storage system
Data Path: Focuses on engineering a highly distributed, latency-critical Hot I/O Data Path and Element Store engine. This role is responsible for the ingestion, state-of-the-art compression, encoding, and retrieval of multi-protocol data (files and objects) under massive concurrency and ultra-low latency requirements.
Database: Focuses deeply on core relational database internals, specifically designing low-level storage engines, B-Tree/LSM-Tree data structures, MVCC concurrency control, and query execution planners.
Kernel: Focuses on the lowest software layers, emphasizing Linux Kernel development and block-level storage/file system engineering.
Protocols: Focuses strictly on engineering high-concurrency data/metadata paths that replicate external AWS S3 object-storage behavior and correctness under heavy retry and failover pressure.
Cloud: Focuses on cloud-native storage deployment, adapting and scaling complex high-availability storage infrastructure across major hyper-scaler cloud environments (AWS, Azure, GCP).
Compute Kafka: Focuses on distributed event-streaming and messaging platforms, specifically building a high-scale, exactly-once broker compatible with the Apache Kafka wire protocol.

Shape the Future of AI Infrastructure with our company
This is a rare opportunity to join one of the fastest-growing infrastructure companies in tech history, right at the epicenter of the AI revolution.
Recognized by Forbes as "the future of the market," we are building the foundational enterprise software powering the AI era. We engineer platforms that capture, catalog, refine, and protect massive datasets across data centers, edge, and cloud, making real-time analytics, AI training, and inference simpler and faster than ever before.
Our explosive growth is fueled by relentless engineering innovation, a customer-first mindset, and a team of fearless workers who thrive on solving computing's hardest problems. Join us at this pivotal moment in technology history and make a lasting impact on how the world processes data.
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 storage platform.
Build scalable and resilient distributed services handling petabytes of data across large clusters.
Participate in architecture discussions around consistency, replication, fault tolerance, and system scalability.
Investigate and resolve complex production issues spanning storage, networking, distributed services, and operating system layers.
Collaborate closely with architects, researchers, and engineering teams to deliver high-performance data infrastructure powering AI, analytics, and enterprise workloads.

As a Backend Software Engineering, your job responsibilities will include:
Build and ship high-quality, production-grade software using modern engineering practices, with AI as a core part of your development workflow by pushing the boundaries of AI development tools to deliver secure, optimized, and high-quality code.
Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale.
Contribute to building and maintaining the shared system context, an explicit repository of system designs, constraints, and standards that enables AI to operate accurately and reliably.
Critically evaluate code (human or AI-generated) for correctness, quality, security, and performance.
Build new and exciting components in an ever-growing and evolving market technology to provide scale and efficiency.
Develop high-quality, production-ready code that can be used by millions of users of our cloud platform.
Make design decisions on the basis of performance, scalability, and future expansion.
Work in a Hybrid Engineering model and contribute to all phases of SDLC including design, implementation, code reviews, automation, and testing of the features.
Build efficient components/algorithms on a microservice multi-tenant SaaS cloud environment
Code review, mentoring junior engineers, and providing technical guidance to the team (depending on the seniority level).

We are seeking an experienced engineer to join our team that owns the network stack for EC2 distributed AI/ML systems. The team develops support for a variety of frameworks and communication libraries including NCCL, NVSHMEM, NIXL, NCCL GIN, and Perplexity kernels. Solid knowledge of Linux, networking, and performant coding is important. Experience with embedded systems is valued, and experience with high-speed networking or HPC/RDMA interconnects is highly valued.

If you like solving hard problems, want to work with HPC and ML customers, iterate fast and deliver meaningful solutions at scale, then come join us! This truly is a role at the forefront of AI/ML-you'll be working on features for the largest clusters, with the largest customers, for the largest AI models.

Key job responsibilities
Be a senior engineer on a team that builds and maintains the infrastructure that monitors and reports on functionality and performance of massive testing workloads run at scale. Use our internal CI/CD tools, Linux, and public AWS products to automate the delivery of our software to customers, saving developer time. Write Python code that effortlessly spools up large clusters and runs benchmarks and applications for ML and HPC workloads. Use AWS Managed Grafana and Athena to digest the massive amount of performance data generated by these workloads and create dashboards for developers and stakeholders. Invent automatic mechanisms to alert developers to functional and performance regressions so they never reach reach customers. Manage the complexity of infrastructure that covers many instance types, software stacks, Linux operating systems, cutting-edge releases and make it easy to evolve.

As a Senior or Principal Software Engineer in Cortex Cloud, you will contribute to the development and scaling of cloud-native security solutions for enterprise organizations. This role involves working within an established team to evolve a high-traffic product, with a focus on refining architecture, optimizing the technology stack, and maintaining engineering standards.
Your responsibilities include writing reliable code, influencing product direction, and designing distributed systems. You will be expected to make technical decisions that impact the long-term stability and performance of cloud workload protection services.
AI Integration & Engineering Workflow
A core component of our development process is the use of AI. Rather than basic code completion, we integrate AI assistants as functional components of our workflow. Our team utilizes a multi-agent AI system (IDEX/ProDex) that assists across the development lifecycle: from planning and architecture to code analysis and security reviews.
In this role, you will:
Work with AI Tools:Utilize platforms such asGemini, Claude, and Cursorfor tasks beyond code generation, including root-cause analysis, system design reviews, and architectural assessment.
Develop AI-Augmented Workflows:Help refine how AI is integrated into the SDLC, including the orchestration of agents and the development of internal tools that extend AI capabilities across our codebase.
Maintain Quality Standards:While AI assists in increasing velocity, you are responsible for the technical output. This includes critical review of all generated code and ensuring that AI-assisted work aligns with our architectural requirements and security benchmarks.
Interact with Specialized Agents:Coordinate with AI agents (Product, Architecture, Security) that operate on shared context to assist in managing complex engineering tasks.
We are looking for engineers who are interested in leveraging AI as a technical tool to manage complexity and who want to contribute to the practical application of human-AI collaboration in a cloud environment.

As a Senior or Principal Software Engineer in Cortex Cloud, you will contribute to the development and scaling of cloud-native security solutions for enterprise organizations. This role involves working within an established team to evolve a high-traffic product, with a focus on refining architecture, optimizing the technology stack, and maintaining engineering standards.
Your responsibilities include writing reliable code, influencing product direction, and designing distributed systems. You will be expected to make technical decisions that impact the long-term stability and performance of cloud workload protection services.
AI Integration & Engineering Workflow
A core component of our development process is the use of AI. Rather than basic code completion, we integrate AI assistants as functional components of our workflow. Our team utilizes a multi-agent AI system (IDEX/ProDex) that assists across the development lifecycle: from planning and architecture to code analysis and security reviews.
In this role, you will:
Work with AI Tools: Utilize platforms such as Gemini, Claude, and Cursor for tasks beyond code generation, including root-cause analysis, system design reviews, and architectural assessment.
Develop AI-Augmented Workflows: Help refine how AI is integrated into the SDLC, including the orchestration of agents and the development of internal tools that extend AI capabilities across our codebase.
Maintain Quality Standards: While AI assists in increasing velocity, you are responsible for the technical output. This includes critical review of all generated code and ensuring that AI-assisted work aligns with our architectural requirements and security benchmarks.
Interact with Specialized Agents: Coordinate with AI agents (Product, Architecture, Security) that operate on shared context to assist in managing complex engineering tasks.
We are looking for engineers who are interested in leveraging AI as a technical tool to manage complexity and who want to contribute to the practical application of human-AI collaboration in a cloud environment.

We are looking for a highly skilled Real-Time C++ Engineer who embodies ambition and positivity - someone who takes ownership of complex, performance-critical problems and collaborates effectively with remote and on-site teams to meet and exceed our objectives and fulfill the evolving needs of our expanding customer base.
The Real-Time C++ component is at the core of our Quantum Orchestration Platform - it serves as the driver for the Pulse Processing Unit (PPU), our proprietary VLSI-based engine. This component is responsible for preparing, loading, and launching the execution of quantum-computing workloads, operating at extreme performance levels to maximize hardware utilization and minimize software overhead.
Responsibilities:
Develop and maintain the real-time C++ layer that drives the Pulse Processing Unit (PPU), our proprietary VLSI-based processor.
Design and implement high-performance software for preparing, loading, and launching quantum-computing workloads with minimal latency and maximal hardware utilization.
Drive relentless optimization of the software stack to minimize SW overhead in the critical path, ensuring the hardware operates at peak throughput.
Collaborate closely with VLSI, compiler, and architecture teams to ensure seamless software-hardware integration across the quantum control stack.
Contribute hands-on to the codebase - designing, implementing, reviewing, debugging, and profiling performance-critical code paths.
Uphold the team's engineering standards, code quality practices, and performance benchmarking methodologies, and help raise the bar over time.
Participate in technical planning and roadmap discussions, aligning your work with product and customer needs.

we are looking for a Senior Software Engineer - Cloud Security.
Your Role:
Design, develop, and maintain complex, scalable, and high-performance systems with a focus on writing clean, efficient, and maintainable code.
Collaborate with cross-functional teams, including product managers and architects, to implement technical solutions aligned with business objectives.
Provide input on architectural design and participate in technical planning to ensure long-term maintainability and compliance with standards.
Identify and troubleshoot production issues, conducting root cause analysis and implementing fixes to ensure system reliability.
Contribute to code reviews and technical discussions, sharing knowledge and fostering a culture of collaboration and continuous improvement.

This role is a great fit for engineers who thrive on low-level, performance-sensitive problems, and want to shape the future of observability through cutting-edge kernel technology.
At our company, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them.

What Youll Do:
Design and build core components of our zero-instrumentation APM product using eBPF and Go
Develop systems to auto-discover services, classify L7 protocols, and extract RED metrics from both plaintext and TLS traffic
Solve complex challenges around protocol parsing, encryption handling, and performance at the kernel level
Ensure broad compatibility across Linux kernel versions, distributions, and diverse customer environments
Collaborate across teams to drive technical direction, improve reliability, and scale the system for production use