דרושים » תוכנה » Sr. DevOps Engineer

We are looking for a Junior SW Development Engineer to join our team.
You will be based in Caesarea, Israel.



Location
Hybrid - Working at least 3 times a week from the office



What you will be doing:

As a member of one of our global Agile SW Scrum teams, you will contribute to the development of cutting-edge, cable industry-leading products and services.
Your work will involve:

C/C++ Software Development: Design and implement features within the MAC and upper layer protocol domains, leveraging the latest advancements in C++ technology.
Advanced Networking Solutions: Contribute to solutions running on Linux servers using containerized environments (Kubernetes), employing state-of-the-art technologies and methodologies.
Troubleshooting & Debugging: Investigate and resolve complex issues from internal QA teams and external customer reports.
Agile Methodologies: Plan, develop, and deliver features in an Agile development environment.

We are looking for a Senior Software Engineer to help build and optimize large-scale, high-performance GenAI infrastructure and inference systems on Kubernetes.
As AI workloads increasingly move toward Kubernetes-native infrastructure, we are building systems that support distributed inference, performance optimization, reliability, observability, and production-grade deployment at scale.
This role is ideal for an engineer who can reason deeply about systems, performance, tradeoffs, and reliability, and who is comfortable owning difficult technical decisions end-to-end.
You will work across inference serving, distributed systems, optimization, and Kubernetes-native AI infrastructure.
What Youll Do:
Build and optimize high-performance Kubernetes-native GenAI inference systems
Work with modern inference stacks such as vLLM, SGLang, TensorRT-LLM, and related tooling
Work with Kubernetes-native distributed LLM inference frameworks such as llm-d and NVIDIA Dynamo
Design and implement optimization algorithms and performance improvements
Improve reliability, observability, deployment, and operational maturity of AI systems
Make architectural decisions and take ownership of technical outcomes
Collaborate with a small, senior engineering team focused on performance and production quality

we are looking for a Senior Machine Learning Engineer to work on LLM-based systems with a strong emphasis on integration, end-to-end workflows, and production readiness. This role combines performance optimization (prefill/decode, throughput, latency) with hands-on work integrating components across the AI platform.
A significant part of the role involves building end-to-end integration flows and tests, particularly around token generation pipelines and system orchestration, as well as contributing to intelligent system behavior such as hardware selection and execution strategies. The role also includes developing system-level logic in Python for multi-tenant management, caching strategies, and service lifecycle management across the platform.
***This is not a Data Science position***
Responsibilities:
Build and maintain end-to-end integration flows across the AI inference pipeline (serving, orchestration, APIs, and infrastructure)
Design, implement, and optimize LLM inference workflows, including prefill and decode stages
Improve system performance with focus on throughput, latency, and interactivity
Write production-grade components in Python and integrate them into the broader system
Contribute to system-level logic such as smart hardware selection and execution strategies
Integrate models (open source and custom), services, and APIs into cohesive, reliable end-to-end application pipelines

we are seeking a Lead System Architect to join our system architecture team and help define the next generation of our AI-SuperNIC scale-out chip.
AI scale-out communication is a critical element in modern data centers, and emerging standards such as Ultra Ethernet aim to address this challenge. This role focuses on defining a high-performance Smart NIC architecture optimized for GPU-centric AI workloads, with emphasis on low-latency, high-bandwidth data movement.
You will work across hardware and software domains, collaborating closely with AI, platform, driver, and VLSI teams to design a competitive scale-out networking solution.
Responsibilities:
Lead the software architecture and technical roadmap for or next-generation ultra low-latency AI-SuperNIC software stack, including drivers, firmware, libfabric, and libibverbs.
Define the partitioning and interfaces between hardware, firmware, kernel drivers, user-space libraries, and AI frameworks.
Lead the design and implementation of high-performance networking, RDMA, and GPU-direct communication capabilities.
Drive software support for emerging technologies and standards such as UEC, UALink, MRC and RoCEv2 ecosystems.
Work closely with hardware, system architecture, and VLSI teams to optimize performance, scalability, and feature delivery.
Define performance goals and lead profiling, benchmarking, and optimization efforts for GenAI and distributed AI workloads.
Collaborate with customers, partners, and open-source communities to ensure ecosystem compatibility and adoption.
Mentor software engineers and provide technical leadership across firmware, driver, and networking software development

As a growing startup, this role will continue to evolve, and were looking for team members who are comfortable building operational processes that scale with the company.

The Operations Lead is responsible for end-to-end execution of customer deployments, owning all non-engineering aspects of delivery across pilots, initial deployments, and scaled rollouts. This role operates within a cross-functional scrum led by a Field Deployment Engineer (FDE), ensuring projects are delivered on time, at quality, and at scale.

Responsibilities:

Own end-to-end deployment execution, including planning, timelines, and rollout strategy
Drive project plans, milestones, and execution tracking across multiple workstreams
Manage field operations, installers, vendors, and site readiness
Coordinate cross-functional teams (Engineering, Product, Sales, Customer Success)
Act as the operational point of contact for customers during deployments
Identify and mitigate risks, ensuring on-time delivery and high-quality execution
Own logistics and onsite readiness for pilots, deployments, and rollouts
Build scalable processes, templates, and best practices for deployment operations

As SW Engineer you will participate in software development of a state-of-the-art medical robot, in a fast growing and dynamic environment.

Your day-to-day will include all stages of software development lifecycle - requirements definition, design, implementation, integration, testing and maintenance.

Main Responsibilities:
Participate in the full development cycle - specification, design, deployment and maintenance of a wide variety of SW modules (these include - UI/UX, 2D and 3D graphics, Robot communication protocols, application services and business logic and more.
Provide ongoing maintenance, support and enhancements in existing systems and platforms.
Collaborate cross-functionally with data scientists, business users, project managers and other engineers to achieve elegant solutions.
Provide recommendations for continuous improvement.
Work alongside other engineers on the team to elevate technology and consistently apply best practices.
Document processes and maintaining software development records, following the software development lifecycle.
Maintain and improving existing codebases and peer review code changes.

Main Responsibilities:
Manage, planning and execution of components level and E2E system tests with documented test results.
Participate in the verification and validation testing of the current and future products.
Ownership of designing, planning, and writing verification and validation testing documentation for existing and future products/features/modules, according to requirements.
Provide effort and time estimations of testing process for existing and future products/features/modules.
Lead the maintenance and definition of SW life-cycle related tasks including documentation and other regulation related issues.
Collaborate with Development, Applications, Project Management and Customer Support team members throughout the lifecycle of a project/product.
Assist other testing engineers with testing assignments and/or training.
Participate in customer and field issues support investigation.

we are looking for a sharp, hands-on Product Manager to help define NR-NEXUS, our next-generation AI inference platform.
This role is ideal for experienced product manager who is fast-learning, technical, and ambitious. Youll work closely with Product, R&D, Marketing and customers engineering team to turn market needs, customer feedback, and AI infrastructure trends into clear product requirements, workflows, demos and PoCs.
What Youll Do:
Help define NR-NEXUS product capabilities, workflows, and use cases
Write clear PRDs, user stories, feature briefs, and competitive notes
Research AI infrastructure, SaaS platforms, model serving, and inference trends
Work with engineering to translate technical capabilities into product value
Support customer and partner discovery with sharp product thinking