דרושים » אבטחת איכות QA » Senior Identity integrator Engineer

We are looking for a QA Data Automation Engineer to join our Data Team in a dynamic and challenging role, providing critical test coverage for our data pipelines, reporting layers, and analytics solutions.
In this role, you will be responsible for validating data integrity end-to-end - from raw ingestion and transformation layers to dashboards and downstream consumers. You will design and maintain automated tests to ensure accurate, reliable, and scalable data systems.
Key Responsibilities:
Develop and maintain automated QA tests for data pipelines, transformations, and data products.
Perform and execute manual QA testing such as functional, regression, and sanity testing of applications, dashboards, and backend systems.
Validate data flow across the system, including: ingestion, transformations, reports/dashboards.
Perform data quality testing (completeness, consistency, accuracy, timeliness, schema validation).
Write and execute SQL-based tests to validate logic, joins, aggregations, metrics, and anomalies.
Build automation frameworks and validation scripts using Python.
Work closely with Data Engineers and Analytics/BI stakeholders to define test coverage and acceptance criteria.
Investigate failures and data issues, providing clear RCA and actionable bug reports.
Document test plans, test scenarios, expected results, and automation coverage.
Track issues in Jira, including reproducible steps and supporting evidence.
Continuously improve QA processes for better monitoring, reliability, and faster releases.

XM Cyber is a global leader in hybrid cloud security. XM Cyber brings a new approach that uses the attacker’s perspective to find and remediate critical attack paths across on-premises and multi-cloud networks. The XM Cyber platform enables companies to rapidly prioritize and respond to cyber risks affecting their business-sensitive systems. We are looking to hire a Senior QA Automation Engineer to join our team at this exciting stage of our companys growth. What You’ll Do Architect & Build: Lead the design of automation frameworks focusing on Component Testing and E2E flows Cloud Integration: Orchestrate automated test environments that deploy our services onto AWS using Docker (and ideally K8s Pipeline Ownership: Fully integrate test suites into our GitHub Actions CI/CD pipelines. Strategy & Mentorship: Create comprehensive test plans and mentor junior/mid-level team members on automation best practices. API Excellence: Maintain and expand our Rest Assured API automation suite.

Ww are looking for an Experienced QA Engineer to write test scenarios, automating test flows and execute manual test plans for web applications! We are looking for people who look at the world differently, people who are passionate about making sense out of huge amounts of data, who explore, analyze and lead the solutions they envision. If you are an engineer that is passionate about being part of an innovative product, making an impact, and striving to work with the industrys best talent as part of one of the fastest growing and successful startups around - this is where you want to be!
So what will you actually be doing?
Design, plan, analyze QA tests/test-plans for web applications.
Work closely with the development teams and be part of a development cycle.
Design and execute automated end-to-end regression and sanity tests, identifying gaps and deficiencies.
Assess delivery readiness and maintain outstanding UX/UI standards through manual testing as needed.
Investigate product quality issues to uphold high-quality standards.
Collaborate with Product and other teams to manage documentation and ensure timely releases.
Review final product functionality before releases.
Assist and guide developers in creating test plans for their new features.

Required People Infrastructure Lead (Systems, Data & Compensation)
About The Position
What this role is:
Think of this as the platform engineering role for our People function. Just like a platform team builds the systems that let engineers ship fast - you'll build the operational layer that lets the entire company run fast.
Real-time data. Automated workflows. Compensation logic that actually scales. No legacy systems to untangle, no inherited processes to maintain. Full ownership over how People infrastructure gets designed, built, and operated.
This isn't traditional People Ops. It's the technical backbone behind it.
What you'll build:
Own the People infrastructure end-to-end - HiBob and the integrated ecosystem around it.
Engineer frictionless, automated lifecycle workflows across the entire employee journey - from offer to offboarding.
Build the compensation infrastructure from the ground up: leveling, salary bands, benchmarking, and the logic that ties them together.
Turn organizational data into a real-time, high-fidelity source of truth that leaders actually trust.
Deploy AI and automation to eliminate manual work - not assist it.
Give leadership the visibility and operational agility to make fast, confident decisions at any scale.
These are the core domains. What you build within them and how - is largely up to you.
You'll thrive here if
You've built People systems from scratch - not maintained someone else's.
You think in systems and data, not tickets and tasks.
You're technically comfortable - you can turn a People challenge into an automated workflow without waiting for IT.
Compensation logic excites you, not intimidates you.
You've worked in a high-growth environment and know exactly what breaks at scale.
You're excited by using AI to replace manual work - not just dress it up.
You move decisions forward instead of getting stuck in discussions.

Required Al Infrastructure & Reliability Engineer
What this role is really about
Youll join a 3-person platform team within our Business Technology group -owning the internal infrastructure that our AI platform and its users depend on. This isnt a product engineering role, and it isnt ticket work or babysitting pipelines someone else built. Youre building and operating the internal foundation that the company runs on. The work covers the full stack of platform engineering: core cloud infrastructure (AWS, Kubernetes, IaC), CI/CD pipelines, AI-driven infrastructure components, and the SRE and observability practice that keeps it all honest -metrics, alerting, incident response, and reliability standards. As our AI capabilities grow, so does the complexity underneath them, and staying ahead of that is central to the role. If you treat infrastructure as a product -reusable, automated, observable, and built to last -this is your kind of role.
Job responsibilities
DevOps & AI-Driven Infrastructure - own CI/CD, deployment processes, and release reliability. Build and operate cloud infrastructure that is automated, intelligent, and continuously self-improving - not just managed.
Design and build our Terraform repository and IaC pipeline from scratch -AI-assisted generation, drift detection, and policy enforcement built in.
Build AI-driven GitHub Actions pipelines -automated code review, risk assessment, and intelligent deployment decisions.
Manage Kubernetes workloads across AWS accounts -zero downtime, fully automated, nothing left behind.
Embed AI into the operational layer -proactive drift detection, automated remediation, and intelligent scaling toward a self-healing runtime.
Reliability & SRE -improve uptime, resilience, and incident response.
Define and enforce SLOs/SLIs, error budgets, and on-call practices.
Lead incident response, postmortems, and systemic reliability improvements.
Own AI-specific reliability: model latency SLOs, token quota monitoring, rate limit handling, fallback and retry strategies, and cost-per-request alerting.
Observability & Telemetry - increase visibility, reduce noise, improve troubleshooting.
Establish and continuously evolve the observability stack: metrics, logs, distributed tracing, and alerting tuned for both application and AI workloads.
AI / LLM Operations- bringing AI systems to production and operating them at scale, with a focus on reliability, performance, and trust.
Own the AI infrastructure layer: rate limits, quota management, latency SLOs, and fallback strategies (retries, circuit breakers).
Operate LLM APIs in production with resilience and cost attribution per team/model.

we are looking for a CI and Automation Engineer.
As a CI and Automation Engineer leading our Release efforts, you will bridge the gap between pure DevOps/Automation and the final delivery of our AI software stack. You wont just be building pipelines; you will be the technical owner of the release cycle, architecting the automation and branching strategies that ensure our firmware and software are production-ready.
You will act as the Technical Gatekeeper, using your deep-dive coding skills in Python and Bash to build the infrastructure of trust that powers our releases. This role is for a hands-on engineer who wants the strategic responsibility of making the Go/No-Go call based on the very automation they have built. If you are passionate about CI/CD excellence and want to see your code directly impact the delivery of world-class AI hardware, this is the role for you.
Responsibilities:
Release Ownership: Lead the technical execution of release cycles, acting as the primary authority and Gatekeeper for software and firmware delivery.
CI/CD Engineering: Design, implement, and maintain robust CI pipelines (e.g., Jenkins, Bitbucket) tailored for release stability and automated validation.
Hands-on Automation: Develop and maintain tools and scripts (Python, Bash) to automate the entire release flow-from versioning and branching to automated reporting.
Technical Triage: Deep-dive into build failures and integration issues. Analyze logs and code changes to make data-driven Go/No-Go decisions.
Branching Strategy: Define and manage complex Git strategies to ensure smooth integration across multiple versions and hardware targets.
Visibility & Reporting: Provide real-time visibility into release health and quality metrics through dashboards and automated status reports.