דרושים » הנדסה » Director of Engineering

We are looking for a visionary engineering leader to architect and lead our quality engineering discipline into the AI era. You will own automation infrastructure, performance engineering, and all AI-driven quality initiatives - building and mentoring high-performing teams of engineers and architects who set the standard for how modern software is validated at scale.
This is not a maintenance role. You will disrupt legacy testing paradigms, champion agentic test generation, and embed AI-quality thinking into every stage of the SDLC - from the first commit to production monitoring. You will be the organizational bridge between engineering velocity and product reliability.
How will you make an impact?
AI Quality Strategy
Define and lead all AI-augmented quality initiatives across the organization
Deploy LLM-powered test generation, triage, and root-cause analysis tooling
Build frameworks for validating AI/ML model outputs and non-deterministic behaviors
Evaluate and integrate emerging AI quality toolchains (GitHub Copilot, Claude, agents)
Champion responsible AI testing practices, coverage standards, and governance models
Automation Engineering
Own the full automation strategy across UI, API, and integration layers
Architect scalable, maintainable test frameworks
Drive shift-left testing embedded in CI/CD pipelines (Jenkins, GitHub Actions)
Establish coverage KPIs, flakiness SLAs, and automation ROI metrics
Lead adoption of self-healing and AI-assisted test maintenance
Performance Engineering
Lead performance and load testing strategy at enterprise scale
Define SLOs/SLAs and partner with SRE on reliability thresholds
Design continuous performance validation integrated into delivery pipelines
Drive root-cause analysis for regressions, bottlenecks, and latency spikes
Oversee toolchain including k6, JMeter, Gatling, and APM integrations
People & Org Leadership
Lead and grow teams of automation engineers, performance engineers, and architects
Set technical direction, OKRs, and career ladders for the quality engineering org
Hire senior ICs and architect-level talent; build succession depth
Foster a culture of ownership, engineering craft, and continuous learning
Partner cross-functionally with Product, DevOps, and R&D leadership.

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.

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.

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.

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.

You will take ownership of the search infrastructure for Ask us - a financial intelligence platform powered by LLMs. Your main goal is to ensure our AI agents can find the exact financial data they need (articles, transcripts, news) in milliseconds. You will work on the Retrieval layer of our RAG architecture, combining traditional text search with modern vector search techniques.

Tech Stack: Elasticsearch (v8+), Python (FastAPI, Asyncio), OpenAI Embeddings, LangChain, LangSmith.

What You'll Do:
Search Engine Development: Design and implement Hybrid Search strategies. You will figure out how to best combine "keyword matching" (finding specific tickers like 'AAPL') with "semantic search" (finding concepts like 'revenue growth').
Relevance Tuning: You are responsible for the quality of search results. You will build systems to measure and improve how well the search engine answers user queries (using tools like LangSmith).
Vector Search & RAG: Manage the integration of OpenAI embeddings into Elasticsearch. You will solve challenges related to indexing long documents (e.g., earnings transcripts) so the AI retrieves only the most relevant parts.
Performance Optimization: Optimize Elasticsearch queries and index settings to ensure low latency, even for complex queries with many filters.
Python Backend: Develop and maintain the Python services that build queries and process results. We use FastAPI and Asyncio heavily.

We're looking for a Data Science Tech Lead to take technical and delivery ownership of this team, a hands-on senior IC role. You'll set research direction, own client-facing delivery end-to-end, and drive how the team builds and scales its use of GenAI tooling and agentic capabilities. You'll work closely with other data scientists & analysts and partner daily with Solutions, Implementation, and Engineering. This role comes with real latitude to shape research direction and influence our product offering and roadmap - not just execute against a backlog.

What you will do
1. Research Direction

Set the technical research agenda for our tabular prediction models.
Guide how we incorporate temporal signal - case history, lag features, schedule snapshots- without defaulting to time-series techniques that don't fit our data.
Own our strategy for extracting value from unstructured data sources via LLMs - feature extraction, embeddings, or fine-tuning - balancing accuracy, cost, and constraints like latency and privacy.
Set standards for experimentation, evaluation, and model guardrails.
2. Client Project Delivery

Own DS delivery end-to-end across concurrent client engagements - from discovery through modeling, validation, and go-live.
Partner with Solutions and Implementation on discovery and rollout; represent Data Science in client meetings, presenting results directly to stakeholders.
Ensure delivery lands inside the product, on timeline, coordinating with Engineering on productionization.
Track delivery risk across the client portfolio, flagging blockers and scope changes early.
3. GenAI Tooling & Team Capability

Build the team's onboarding and delivery playbook for new use-cases and encode it as reusable Claude skills/agents
Turn repeatable steps in the DS workflow into standardized, shared tooling.
Raise the team's GenAI fluency through mentoring on Claude Code and related tooling.