לוח משרות דרושים מנהל איכות | מנהל QA משרה מלאה, לחיפוש זה נמצאו 91 משרות

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.

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.

We are looking for a Quality & Reliability Lead
Role Description
The Quality & Reliability Engineer is responsible for driving product quality, manufacturing excellence, and reliability performance across our products and operations.
Working closely with Engineering, Manufacturing, Supply Chain, Service, and R&D teams, this role leads quality and reliability initiatives that improve process capability, manufacturing yields, product robustness, and customer satisfaction through data-driven decision making, structured problem solving, and continuous improvement methodologies.
The role is also expected to leverage AI and advanced analytics tools to accelerate insights, improve decision making, and enhance operational effectiveness.
Responsibilities
What will you be doing:
Responsibilities - Quality
Lead quality improvement initiatives focused on yield enhancement, defect reduction, process stability, and continuous improvement across DMD operations.
Establish and maintain Statistical Process Control (SPC) and drive process capability analysis using statistical methods and data-driven quality metrics.
Lead root cause investigations utilizing methodologies such as 8D, 5 Why, Fishbone Analysis, Pareto Analysis, DOE, and FMEA.
Drive NCR, CAPA, and corrective action processes, identify trends, prioritize actions using evidence-based analysis, and verify effectiveness of implemented solutions.
Partner with Manufacturing, Engineering, Service, and Customer Support teams to resolve product quality issues, customer complaints, field incidents, and escalations.
Collaborate with suppliers to improve quality performance, drive supplier corrective actions, and reduce supplier-related quality risks.
Conduct supplier audits and assessments, including evaluation of manufacturing controls, process capability, inspection methods, and process discipline.
Review supplier quality documentation including CoC, CoT, ATR, inspection records, and quality reports to identify risks, trends, and improvement opportunities.
Lead internal and external audits, ensuring compliance and effective corrective actions.
Responsibilities - Reliability:
Partner with Engineering and R&D teams to define reliability qualification plans, test strategies, acceptance criteria, and reliability requirements for new and existing products.
Ensure reliability testing programs are properly executed and that test results are systematically reviewed, analyzed, and translated into actionable improvements.
Partner with Service and analyze reliability, field performance, MTBF, and MTTR data to identify trends, emerging risks, and improvement opportunities.
Lead investigations of reliability failures and support identification of physical, mechanical, electrical, optical, material, and process-related failure mechanisms.

We are looking for a QA Manager to own a new testing domain, which enables our products to meet the industry leading benchmarks of efficiency and quality. The ideal candidate will able to learn new features, execute manual/automated tests and be technical expert to the team

What youll be doing:

Lead the QA team from the planning stage through execution up to GA release, with the highest quality for the company`s products.

Collaborate with peer engineering teams, and program/product management to ensure that product requirements, goals and objectives are met or exceeded.

Lead and implement analysis, debugging tracking flows with accordance to QA and SW methodologies.

Review the teams test-plans for the product coverage and strive for full automation.

Report bugs found during execution, assist with reproduction and debugs to understand root cause, verify bug fixes provided by R&D team.

Mentor and guide the professional and technical development of the team members.

Review and identify improvement opportunities in established processes, infrastructure, and practices to ensure the teams are performing in the most efficient way.

We are seeking an experienced and hands-on engineering leader
to drive product quality, reliability, and performance across NPI, manufacturing, and the installed base. The role serves as a technical focal point for complex multidisciplinary issues, leading investigations, task forces, and improvement initiatives that enhance product quality , manufacturing readiness, and customer satisfaction.
What Will You Do?
Product Quality and Reliability:
Own product quality and reliability performance across NPI, manufacturing, and the installed base.
Define, monitor, and analyze quality metrics, reliability indicators, and field performance trends.
Consolidate quality and performance data from internal operations, contract manufacturers, and field systems into actionable insights and management dashboards.
Lead root-cause investigations and corrective/preventive actions (CAPA) for high-impact product and field issues.
Identify systemic issues, prioritize improvement opportunities, and drive cross-functional execution plans to improve product quality, reliability, and customer experience.
NPI, Manufacturing & Installed Base Support:
Drive quality and reliability readiness throughout NPI, validation, and production ramp-up activities.
Lead investigations into complex production, integration, and field failures involving multidisciplinary system interactions.
Partner with Manufacturing, Service, Operations, and Supply Chain teams to improve product stability, serviceability, and operational performance.
Drive implementation of calibration, alignment, validation, and test methodologies that improve quality, consistency, and manufacturing efficiency.
Support contract manufacturers and production teams in resolving critical technical and quality-related challenges.
Continuous Improvement & Change Management:
Lead engineering improvement initiatives based on production performance, customer feedback, reliability data, and field experience.
Drive product robustness, manufacturability, serviceability, and lifecycle performance improvements.
Own execution of Engineering Change Orders (ECOs), product structure management, and change implementation through CCB processes.
Lead periodic product performance reviews and drive closure of improvement actions across functions.

We are becoming an agentic ITSM leader - and we're rebuilding R&D to match. In our AI-native model, a managed, always-on "Machine" produces most of the code while small pods of engineers, PMs and designers direct, review, and govern it. In that world, quality isn't a phase - it's how the system is built.
We're hiring a Quality Lead to own that.
Why this role is different: you won't run a traditional QA team that tests features at the end. You'll own the quality gates inside the Machine and in production, author the monitoring skills our pods rely on, and hold independent authority to fail the Machine's output. Quality is our north star, and this role sets the bar.
THE MISSION: Make reliability, performance, and user experience a property of the system - not of individual heroics. Build and lead a Quality function (~9 people) that keeps an AI-native delivery org fast and trustworthy, and give the business confidence that what the Machine ships is safe to ship.
WHAT YOU'LL DO:
Own quality gates in the Machine - prose-driven tests (generated from requirements, not the code), adversarial / agent-checks-agent review, static analysis and code-quality remediation (e.g. SonarCloud), and CI gates that run before anything reaches a human.
Own quality in production - release verification, production testing, and ownership of change-fail and deployment-rework rates.
Author monitoring guidelines & reusable observability skills that delivery pods and the Machine consume - so monitoring is built in, not bolted on.
Own the evals that score the Machine's output for behavioral consistency and reliability - treating evaluation as a first-class engineering discipline.
Act as an independent governance voice - with the authority to block or fail output that doesn't meet the bar, partnering closely with Architecture.
Partner with the Core Platform team on the quality of customer-issue fixes and existing functionality.
Lead, coach and grow the team - quality/gate engineers, an agent-evaluation engineer, production-monitoring (SRE) and QA-infrastructure engineers.
Set the quality metrics and report them - DORA + deployment-rework rate, escaped-defect rate, review-queue depth, eval pass rates.
WHAT YOU'LL OWN (OUTCOMES)
Fewer regressions and less firefighting; faster resolution of customer issues.
Reliability, performance and UX that customers can count on.
A quality system trustworthy enough to let autonomous delivery scale safely.