דרושים » תוכנה » Software Engineer - BSP & Firmware

We are seeking a senior ATE Software Engineer to design, build, and deploy our next-generation automated manufacturing test platform for advanced telecom, high-density switching, and optical networking hardware.
In this role, you will bridge the gap between R&D hardware/firmware teams and high-volume manufacturing lines. You will take ownership of ingesting, refactoring, and consolidating disparate R&D scripts, diagnostic tools, and legacy software into a single, scalable, production-grade test platform.
We expect you to leverage modern AI-assisted development tools and workflows to maximize engineering efficiency, accelerate delivery timelines, and build highly robust, self-healing test automation. You will deploy test stations across global Contract Manufacturers (EMS/ODM), actively stabilize production lines through bring-up and ramp-up, and drive continuous test maintenance and root-cause failure analysis (RCA).
Key Responsibilities
Test Platform Architecture & Software Development:
Design, develop, and productize robust, modular test software frameworks for board-level (PCBA) and system-level manufacturing testing across multiple product lines and manufacturing sites.
Codebase Unification & Refactoring:
Consolidate and standardize R&D diagnostic libraries, silicon validation scripts, and firmware tools developed across various environments (Python, C# / Visual Studio, VB, ATEasy, Linux) into a unified, maintainable test execution engine.
AI-Accelerated Development & Workflow Automation:
Actively integrate Generative AI tools and AI coding agents into your daily workflow to accelerate code conversion/refactoring, automate test case synthesis, generate edge-case validation scripts, and enhance overall codebase resilience.
Production Line Deployment & Stabilization:
Deploy test stations and fixtures to local and overseas EMS/CM production lines. Monitor, debug, and fine-tune test execution during NPI and ramp-up phases until yield, takt time, and test stability targets (CPK / First Pass Yield) are achieved.
Failure Investigation & Intelligent RCA:
Investigate complex system-level and component-level test failures. Utilize advanced log analysis, structured telemetry, and pattern recognition to drive root-cause investigations and implement preventive software/hardware fixes.
Ongoing Test Maintenance & Optimization:
Provide continuous operational Production line support and maintenance, bug fixes, software updates, and station cycle-time optimizations for active mass-production lines.
R&D Collaboration & Test Specification:
Collaborate closely with Hardware, Firmware, and Validation teams during early design phases to define test specifications, drive Design for Testability,
Documentation & Technical Reporting:
Author and maintain comprehensive testing documentation, Standard Operating Procedures (SOPs), test coverage matrices, and detailed failure analysis reports.
Manufacturing Systems Integration:
Integrate automated test sequences with CMs SFC/MES/QMS, serialized tracking, and central test log databases.
Log Analysis & Analytics Tool Development:
Design and build dedicated log parsing, data visualization, and diagnostic analytics tools to streamline complex hardware/software debugging, accelerate root-cause analysis (RCA), and drive continuous production line cycle-time and yield optimization.

In this role, you will be a key contributor to the design and implementation of AI Graph Compiler software stack for Neural Processing Units (NPUs). You will take part in defining software architecture, implementing performance-critical components, and enabling efficient execution of advanced neural networks under tight power, memory, and latency constraints.

You will work closely with hardware and system architects, software and hardware engineers, influencing both software and hardware decisions. You will design and implement major parts of NPU embedded solutions, actively promoting AI capabilities to the customers.

What will you do:

Own and design key components of the AI Graph Compiler software stack for NPU-based systems.

Optimize inference performance (latency, throughput, memory footprint, power) for edge deployments.

Collaborate on HW-SW co-design, influencing NPU architecture.

Support IP evaluations and silicon bring-up, root-cause complex HW/SW issues, and influence development methodologies.

Mentor junior engineers and contribute to technical best practices.

We are looking for a DevOps IT Engineer to join our dynamic IT team. This role blends hands-on system administration with modern DevOps practices, focusing on building, automating, and operating scalable hybrid environments across on-prem and cloud platforms.
If you are passionate about automation, cloud infrastructure, and improving developer productivity while maintaining robust and secure enterprise systems - we want to hear from you!
Responsibilities:
Design, build, and operate scalable infrastructure across on-prem environments and cloud platforms (AWS & Azure).
Manage and evolve virtualization platforms such as VMware and KVM (Proxmox).
Implement and maintain cloud infrastructure using Infrastructure as Code (IaC) and DevOps best practices.
Own identity and access management solutions including Azure Entra ID (Azure AD), SSO, MFA, Conditional Access, and directory synchronization.
Manage enterprise endpoint solutions such as Microsoft Intune and MobileIron/IVANTI.
Automate infrastructure provisioning, configuration, monitoring, and operational workflows.
Build and maintain internal tools to improve developer experience and engineering productivity.
Ensure system reliability, performance, and cost optimization across cloud and on-prem environments.
Maintain high security standards, compliance, and operational best practices.
Collaborate closely with DevOps, R&D, Security, and IT teams to support development and production environments.
Develop and maintain clear technical documentation.

In this role, as Embedded Software Team Leader, you will lead a team owning a key part of NPU AI software stack, a complex, multi-layered system spanning the Host (SDK, runtime, APIs, and UMD/KMD drivers) and the NPU IP (embedded firmware). This stack is at the heart of the AI software offering, with deep impact on multiple hardware and software teams ability to execute state of the art LLM, Generative AI and Neural Networks with extraordinary performance. Reporting to the AI Software SDK Senior Team Leader, you will lead a team of creative and result oriented enthusiasts that invent, design, and implement software that enables smooth connectivity between the NPU and Host CPU.



Responsibilities:

Lead and manage the Embedded Software engineering team, ensuring high performance and productivity.

Own the design, development, and implementation of your component within NPU AI software stack, aligned with the AI Software SDK group's technical strategy, architecture, and roadmap and its automated CI and release process.

Collaborate with cross-functional teams to integrate solutions. Provide technical guidance and mentorship to team members.

Ensure project timelines and deliverables are met.

Conduct performance reviews and support professional development of team members.

Collaborate globally with architects, HW teams, NPU teams, and other developer teams

As a Solution Engineer, you will play a pivotal role in designing, deploying, and optimizing our companys Network Cloud AI Infrastructure solutions. This individual contributor role requires a blend of technical expertise, leadership, and hands-on experience to implement cutting-edge solutions for our customers. You will collaborate with sales engineering teams, customers, and cross-functional teams - including Product Management, Solution Architects, Engineering, and Marketing - to define technical requirements, articulate solution value, and ensure successful deployment on-site.
Key responsibilities include guiding customers through the design and deployment process, aligning technical solutions with business needs, and providing critical feedback to improve our companys product offerings. This position demands strong technical acumen, exceptional communication skills, and the ability to lead complex, high-impact projects in dynamic environments.
Responsibilities:
Design and plan rack layouts and network topologies to support customer requirements.
Perform Data Center upgrades and ensure smooth deployment of our company solutions.
Install and configure our company products, ensuring optimal performance and customer satisfaction.
Design and implement compelling Proof of Concept lab setups, run them, and collect and document the results for the field consumption
Develop and deliver HLD and LLD documentation for customer deployments.
Design and evaluate automation scripts for network operations, configuring server and switch fabrics.
Engage with sales teams and customers to ensure success with major opportunities and deployments
Introduce new products to the company sales and support teams and to company customers
Deliver technical trainings and TOIs for support/sales engineers, partners, and customers
Collaborate on product definition through customer requirement gathering and roadmap planning.

In this role, as Senior Team Leader of the AI NPU Simulator, you will lead a Group developing a major part of AI simulation framework, in the core of our AI software offering. The AI NPU simulator enables the execution of state-of-the-art LLMs, Generative AI models, and neural networks with exceptional performance, impacting multiple hardware and software teams across the company.

You will drive the development of robust, scalable, and efficient simulation software, working closely with global Architecture, VLSI, and Software teams to shape next generation of AI solutions.

We are looking for an exceptional hands-on leader with strong technical expertise, proven experience leading software teams, and a track record of delivering complex, state-of-the-art products on time and with high quality. The ideal candidate is execution-driven, innovative, and passionate about building high-performing teams and cutting-edge AI technology.



Responsibilities

Manage and lead two teams (Development + Validation) .

Be accountable for the simulation lifecycle, including architecture, development, validation, and release.

Lead development of advanced simulation models for AI processors.

Own delivery of complex, multi-release roadmaps.

Ensure strong alignment between hardware design, compiler behavior, and simulation models.

Drive system-level correctness and performance accuracy.

Support system bring-up, debugging, and customer-facing activities when needed

We're looking for an AI Workflow Engineer to join our System Architecture group. This is a high-impact role where you'll design, build, and continuously improve AI-powered workflows, agents, and tools that help our architects do their best work - from system design and modeling through documentation, technical decision-making, and review.
Working from within the architecture team, you'll turn the group's real, day-to-day pain points into practical AI-assisted solutions. Your primary focus is system architecture within the software development lifecycle (SDLC), and because architecture touches everything, your work will naturally extend into adjacent stages wherever AI can add value.
Key Responsibilities:
Design and build AI-powered workflows, agents, and internal tools that support system architecture work - design, modeling, documentation, architecture decisions, and reviews.
Develop and iterate on agents within our internal framework, using agentic AI techniques to accelerate and augment architecture and engineering tasks.
Continuously improve existing workflows and tools as team needs evolve and AI capabilities advance.
Partner closely with the System Architecture team to understand real pain points and turn them into practical, AI-assisted solutions.
Measure and demonstrate the impact of the workflows you build - for example on design-cycle time, review turnaround, and the quality and completeness of architecture documentation and decision records.
Build proof-of-concept projects that show the practical value of AI in real architecture and engineering workflows.
Develop best practices, prompt engineering guidelines, and reusable patterns for AI-assisted architecture and development.
Stay current with the rapidly evolving AI tooling landscape and advise on strategic adoption.

As a senior compiler engineer, you will own the design and development of open source based toolchain and graph compiler. You will drive technical solutions end-to-end, deliver compiler capabilities across all hardware targets, and help mentor engineers. Our team embraces an AI-agentic development flow, leveraging AI coding agents to accelerate engineering productivity, and we are looking for engineers who champion this approach.

Responsibilities:

Design and develop open source based toolchain targeting custom DSP and NPU architectures.

Drive design and delivery of graph compilation flows: transformations, operator mapping, and code generation.

Champion AI-agentic development practices - integrating AI coding agents into day-to-day engineering workflows.

Own complex components end-to-end, from architecture and design through implementation and delivery.

Provide technical guidance and mentorship to engineers; conduct code reviews.

Collaborate with hardware architecture, algorithms, and software teams globally.

Analyze and optimize toolchain output for performance and correctness across processor families.

Lead a team of compiler engineers responsible for open source based toolchain and graph compiler. You will be a hands-on team leader - driving architecture decisions, guiding engineers, and delivering compiler capabilities across all hardware targets. Our team embraces an AI-agentic development flow, leveraging AI coding agents to accelerate engineering productivity, and we are looking for a leader who champions this approach.

Responsibilities

Lead development of open source based toolchain targeting custom DSP and NPU architectures. Drive design and delivery of graph compilation flows: transformations, operator mapping, and code generation. Champion AI-agentic development practices within the team - integrating AI coding agents into day-to-day engineering workflows. Mentor engineers and conduct code reviews; build a high-quality engineering culture. Collaborate with hardware architecture, algorithms, and software teams globally. Own team planning, prioritization, and on-time delivery of toolchain features. Contribute hands-on to design, implementation, and performance tuning in C++ and Python.