דרושים » מחשבים ורשתות » Senior DevOps Software Engineer - Chip Design

Our team is looking for a Senior DevOps Engineer to join us and take ownership of the CI/CD infrastructure, automation pipelines, and development tooling that power our engineering teams. This position plays a key role in enabling fast, reliable, and scalable software delivery - from code commit to test execution and reporting. You will be the go-to expert for DevOps practices, collaborating closely with software engineers, validation teams, and infrastructure stakeholders across the organization.

What You'll Be Doing:

Design, implement, and maintain CI/CD pipelines for software and validation projects, ensuring fast, stable, and automated delivery workflows.

Own and evolve the DevOps infrastructure - including build systems, artifact management, deployment automation, and environment provisioning.

Develop and maintain automation tools, scripts, and integrations that streamline developer workflows and reduce manual overhead.

Collaborate with validation, infrastructure, and software engineering teams to define and enforce DevOps best practices across the organization.

Monitor system health, pipeline reliability, and build performance; identify bottlenecks and continuously improve observability and stability.

Manage containerization and orchestration solutions (Docker, Kubernetes) for test environments and internal services.

Support the integration of automated testing frameworks into CI/CD flows, ensuring test coverage and results are tracked and visible.

Evaluate and introduce new DevOps tooling and methodologies to keep the team at the forefront of engineering efficiency.

Were looking for a Senior Infrastructure Engineer who views "Infrastructure as Software." In 2026, we dont just manage servers; we build high-performance environments that allow multi-agent systems to operate at scale.
You will be a core member of the R&D team, blending deep DevOps expertise with the coding rigor of a Backend Engineer. You arent just "configuring" AWS; you are architecting the distributed systems and data pipelines that power our autonomous security brain. Your mission is to ensure that while our agents are evolving and taking actions, our underlying platform remains immutable, observable, and infinitely scalable.
What You'll Do
Design, build, and operate our company's cloud infrastructure using AWS, Kubernetes, and Infrastructure as Code.
Build internal tools and platform services using Python and Go to improve developer productivity and system reliability.
Own infrastructure automation with Terraform, Pulumi, and modern cloud-native tooling.
Partner closely with Backend, Data Science, and Security Engineering teams to build scalable, reliable platforms.
Improve observability, monitoring, and incident response across distributed production systems.
Design and optimize infrastructure for performance, scalability, security, and cost efficiency.
Help shape engineering best practices, platform architecture, and developer experience as our company continues to grow.

We are seeking a Network Solution Verification Engineer to join our R&D organization, focused on validating our customer-facing networking solutions at scale using a state-of-the-art End-to-End (E2E) simulation cluster environment.

In this role, you will be a hands-on technical contributor at the intersection of networking, automation, and AI-driven validation - designing and implementing the simulation frameworks, agentic workflows, and regression pipelines that ensure our networking solutions meet the highest standards of quality and real-world applicability before reaching customers.


What you'll be doing:
Designing and implementing end-to-end validation frameworks for our customer-facing networking solutions at scale, leveraging a dedicated E2E simulation cluster environment.
Writing, maintaining, and extending automated test suites and regression pipelines for networking protocols and large-scale simulation runs, ensuring repeatable, high-confidence validation outcomes.
Performing deep regression analysis on simulation results - identifying failure trends, isolating root causes, and delivering clear, actionable findings to architecture and design teams.
Developing agentic AI flows that autonomously perform regression analysis, detect coverage gaps, generate new test cases, and implement validation code - continuously learning from simulation results and product changes to accelerate coverage without manual intervention.
Integrating validation pipelines into CI/CD workflows to enable continuous, automated regression at scale, working closely with DevOps and platform teams.
Collaborating closely with Design, Architecture, and NCS teams to understand solution requirements, translate them into simulation scenarios, and provide early-cycle quality feedback that influences product direction.
Analyzing customer-reported networking issues, mapping them to simulation coverage gaps, and building targeted test cases that prevent regression.
Continuously exploring new simulation technologies, agentic frameworks, and networking standards to evolve and improve the team's validation methodology.

Were looking for exceptional Senior Full Stack Engineers who take full ownership of their work-from technical design through implementation and into real-world usage.
This is a hands-on role for individuals who bring strong engineering fundamentals, curiosity across the stack, and a high standard for quality and reliability.
Youll join a team that values autonomy, deep thinking, and the ability to navigate both frontend and backend challenges.
We expect engineers to care about how their systems behave in production-not just whether they compile-and to help build reliable, scalable software that stands up to real-world demands.
What Youll Do :
Design, implement, and ship end-to-end features spanning web, mobile, backend, and infrastructure layers
Tutor, guide and help to nurture a culture of technical excellence throughout the development organization
Own your code through its lifecycle-from spec and architecture to deployment, monitoring, and evolution
Investigate and resolve issues that arise in staging or production, and help build tools that make doing so easier
Work closely with product and design to define technical solutions that deliver real user impact
Improve system architecture, performance, and development practices over time
Collaborate with peers through code reviews, design discussions, and shared ownership of technical quality

Our Networking System Product Engineering organization is looking for a Senior Data & AI Solutions Engineer - high-agency, self-directed Data & AI Solutions Engineer to partner with engineering teams and transform data, BI, automation and agentic AI into measurable engineering productivity gains.

What youll be doing:
Work closely with engineers, managers, and cross-functional teams to understand complex engineering domains, identify bottlenecks, and build practical solutions that improve decision-making, execution speed, and operational quality.
Develop and deliver production-grade tools, automated workflows, and agentic AI solutions from concept through deployment.
Run fast, high-quality proof-of-concepts on emerging AI and agentic technologies, and productize successful ones.
Implement data flywheels that continuously improve quality through telemetry, benchmarking, automated evaluation, and structured feedback loops.
Collaborate and contribute ideas and code to Product Engineering's evolving data infrastructure.
Improve data quality, integrity, governance, metric definitions, and usability across engineering domains.
Train and enable engineers, managers, and stakeholders to use data, BI, and AI tools effectively.

At our company, "It's all about the user. All of them." We're passionate about providing a seamless one-stop experience for business travelers, no matter how they travel, where they stay, or where they're going. we are building cutting-edge solutions at the intersection of travel, expense, payments, and AI. As a leader in the AI for Travel domain, we are using intelligent, practical AI experiences to make business travel simpler, faster, and more reliable for travelers, travel managers, finance teams, and support teams.
We are constantly striving to make our systems reliable, scalable, and simple to operate so our services are available to travelers when they need them most. With our continued growth, we have exciting challenges ahead and we're looking for a Senior Site Reliability Engineer to join our team in Tel Aviv. This role blends classic SRE ownership with pragmatic AI SRE work: you will build and operate the platforms, automation, observability, and incident response practices that keep our company reliable, while helping teams use AI solutions, AI providers, and their APIs safely and dependably.
This is a hands-on engineering role, not a research role. You will partner with product, platform, data, security, support, and incident response teams to make production systems and AI-powered experiences more resilient. You will use software engineering, infrastructure as code, SLOs, telemetry, provider observability, and automation as your main tools, and you will apply AI where it creates measurable reliability value rather than novelty.
This position is based out of our new Tel Aviv office.
What You'll Do:
Support AI-based application solutions where reliability matters. Partner with the development teams building AI-powered travel experiences to support the development and production operation of their solution.
Work with AI solutions, providers, and APIs. Partner with teams integrating AI capabilities and providers, with attention to API reliability, authentication, quotas, rate limits, latency and provider-specific operational constraints.
Troubleshoot AI tools and provider issues. Diagnose failures across AI-powered workflows, provider APIs, configuration, permission errors, degraded responses and related areas.
Operate reliable production platforms. implement and run cloud infrastructure,and help product teams move quickly without compromising reliability.
Improve observability. Build dashboards, alerts, traces, logs, and runbooks that make service health clear, actionable, and tied to SLOs and customer impact.
Apply AI to SRE workflows. Prototype and productionize AI-assisted systems that create effective and efficient operations
Automate operational toil. Create tools, workflows, and automation that remove repetitive manual work and make operational knowledge easier to use.

We're looking for an exceptional senior Chip Design Engineer to join our Nitro team and help shape what comes next. You'll work alongside a world-class, fast-moving engineering team, take full ownership of critical IP blocks, and see your work deployed at a scale no other platform can match- powering hundreds of thousands of businesses across 190 countries.

As a Senior Chip Design Engineer on the Nitro team, you will take full end-to-end ownership of one or more critical IP blocks within the product, guiding them from micro-architecture definition through RTL design, debug, synthesis, timing closure, and final sign-off before tape-out. Your work will ship in silicon that powers AWS at global scale.
You'll partner closely with the Verification and Emulation teams to shape test plans, review coverage, and close gaps early in the design cycle. Beyond your own IP, you'll collaborate across disciplines with Product Definition, Software, Physical Design, and Verification teams to deliver a fully integrated, production-ready chip.

Key job responsibilities
* Full ownership of one or more IPs within the product:
Micro-architecture definition.
RTL coding and debug.
Synthesis and timing closure.
Sign-off before tape-out.
* Supporting the Verification and Emulation teams: Test plan development, coverage review.
* Ensuring the chip meets quality and reliability standards.
* Collaborating with cross-functional teams, including Product Definition, Verification, Software, and Physical Design.

We are seeking an AI Networking Architect to join the Networking Research Group. This role will help bridge the gap between emerging tasks supported by advanced technologies and the data center infrastructure that powers them. In this role, you will work at the intersection of AI applications, distributed systems, networking hardware, and software architecture.

You will join a focused team of multidisciplinary engineers driving AI workload optimization through deep application understanding, network analysis, and end-to-end systems thinking. Your insights will directly shape our products across the full stack - from applications and software libraries to hardware architecture and physical design.

What Youll Be Doing:

Model the performance of complex AI workloads to identify bottlenecks and recommend system-level optimizations.

Analyze brand-new AI models, distributed training techniques, and inference workloads to understand their infrastructure requirements.

Build Platforms, simulations and HW platforms, execute AI workloads and build analytical tools to evaluate trade-offs across compute, memory, storage, and network behavior.

Translate research insights and workload behavior into actionable software, hardware, and networking architecture requirements.

Partner with architecture, software, and product teams to influence our future networking and AI infrastructure roadmaps.

Drive architectural innovation by applying deep workload analysis to real-world advanced machine learning frameworks.

Integrated Circuit Product Engineering (ICPE) plays a key role in bringing our networking products from early development through production. This role focuses on building the testing infrastructure that helps networking products move from early bring-up through production release, with strong emphasis on power and performance.

What youll be doing:

Architect and build a scalable software-based test infrastructure for networking hardware, with emphasis on power and performance coverage across the product lifecycle from bring-up to production release.

Develop autonomous and agentic workflows that orchestrate test execution, system initialization, measurement, monitoring, logging, data collection, and analysis with minimal manual intervention.

Create the software layers around test content, including scheduling, execution control, telemetry pipelines, result handling, and data processing frameworks.

Integrate lab equipment such as power supplies, thermal solutions, and related instrumentation into a unified automation environment.

Enable high-throughput, high-quality engineering workflows by connecting the infrastructure to CI/CD systems, release flows, and quality gates.

Partner closely with hardware, firmware, product engineering, and lab teams to improve coverage, reliability, and observability across complex networking platforms.

Drive software design and engineering best practices for maintainability, scalability, and long-term platform evolution.