We are looking for an Experienced QA Automation Team Lead with a strong background in designing, developing, and maintaining scalable test automation infrastructures.
Skilled in Python-based test development, modern automation frameworks, API testing, and Playwright for UI automation. Demonstrated ability to lead technical initiatives, guide automation strategy, and integrate innovative testing approaches - including leveraging AI models for intelligent validation, test optimization, and automation tooling. Adept at collaborating across engineering, product, and DevOps teams to improve quality, accelerate releases, and ensure robust system reliability.
Key Responsibilities
Automation Architecture & Infrastructure
Design, develop, and maintain a scalable automation framework using Python, aligned with product architecture and CI/CD pipelines.
Lead the creation of reusable libraries, tools, and test utilities to improve automation efficiency.
Evaluate and integrate new technologies, including AI-assisted test generation, model-based testing, and intelligent failure analysis.
Establish best practices for code structure, version control, and test maintainability.
Test Development & Execution
Build and maintain automated test suites for UI, API, backend, and integration layers.
Implement end-to-end UI automation using Playwright, focusing on reliability and parallel execution.
Develop robust API tests using Python-based tools (e.g., pytest, requests, FastAPI test helpers).
Ensure broad test coverage across functional, regression, performance, and security areas.
Quality Leadership & Strategy
Define the overall automation strategy and ensure its alignment with organizational quality goals.
Lead and mentor QA engineers, providing guidance in Python development, test design, and automation best practices.
Collaborate with product, development, and DevOps teams to refine acceptance criteria and testing standards.
Drive shift-left testing practices and promote automation as a core part of the development lifecycle.
CI/CD & DevOps Collaboration
Integrate automated tests into CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, etc.).
Work closely with DevOps to enable test environments, containerized executions, and scalable cloud-based test farms.
Introduce quality gates and automated blockers to reduce defect leakage and speed up delivery.
AI-enhanced Testing & Innovation
Utilize AI models to enhance test creation, anomaly detection, log analysis, and flakiness reduction.
Develop internal tools using AI for automated test maintenance and failure triage.
Experiment with LLM-driven testing strategies (e.g., agentic testing flows, AI-driven mock generation).

We are looking for an Automation Infrastructure Engineer to join our Automation Infra team and take a key role in designing, scaling, and maintaining the infrastructure that enables all automated testing across our company R&D.
In this role, you will own significant parts of our CI/CD ecosystem, lab environments (Cloud and On-Prem), and automation tooling. You will architect and implement infrastructure solutions that support complex end-to-end testing of a distributed networking and security platform.
Our test environments span multi-layer networking topologies, cloud deployments, ESX-based virtualization, dynamic traffic flows, and advanced security rule engines.
This position requires strong technical depth, broad domain proficiency, and the ability to work across multiple infrastructure areas simultaneously.
Key Responsibilities
Design and architect automation infrastructure, including CI/CD pipelines, integration layers, execution frameworks, and lab-side services.
Build and maintain scalable, reproducible test environments across AWS, Azure, and ESX, including networking, compute, storage, and automation layers.
Develop advanced tooling (Ansible, Terraform, Python, Java) to automate provisioning, orchestration, and lifecycle management of test environments.
Improve reliability and performance of CI/CD workflows, execution pipelines, and environment creation processes.
Collaborate with automation engineers and developers to define infrastructure requirements and deliver solutions that accelerate product validation.
Troubleshoot complex systemic issues across cloud, networking, virtualization, automation frameworks, CI/CD, and distributed services.
Drive best practices for infrastructure automation, observability, scalability, and operational excellence.

Were looking for a visionary Automation Engineer - Networking to join our Automation teams. As a member of this team, you will be responsible for the design, implementation and maintenance of Automated tests using our Java-based framework. Our Automated tests cover various aspects of the product, including complex networking topology, traffic, security rules, and user's authentication scenarios.
Responsibilities:
Define, design, and implement automated regression and sanity tests for our ever-evolving product
Take part in ensuring our product quality and robustness
Identify and design the tools needed for efficient automated testing
Define, set up, and maintain our test automation environments and processes
Develop an Automation infrastructure layer and libraries.

We are redefining the travel industry with a truly autonomous platform powered by proprietary Agentic AI. As an Automation Engineer, youll play an essential part in building and scaling the testing infrastructure that validates our mission-critical AI workflows. This is a high-scale environment where you will use Cypress to solve unique challenges in autonomous decision-making, collaborating globally to deliver a platform trusted by major enterprises.
What Youll Do:
Architect the Cypress E2E Framework: Design, build, and scale a robust, high-performance end-to-end automation framework using Cypress to validate our core web application workflows, ensuring the complex UI accurately reflects the autonomous decisions made by our AI agents.
Validate Autonomous Logic via the UI: Develop sophisticated test harnesses within Cypress that interact with the application and perform data validation (e.g., intercepting network requests) to verify the intricate decision-making, cost optimization, and safety constraints of our self-governing AI agents.
Drive CI/CD Velocity: Take ownership of the testing lifecycle by integrating fast-running, automated Cypress tests directly into our CI/CD pipelines, serving as the final, reliable gate that allows the engineering team to deploy multiple times daily with zero functional regressions.
Performance and API Testing: Utilize Cypress's capabilities for API-level testing to quickly validate backend microservices, augmenting UI tests where necessary to maintain speed and reliability.
Contribute to Engineering Culture: Champion best practices in testability, reliability, observability, and code coverage, mentoring fellow engineers and fostering a culture of technical excellence across the platform.
Solve Unique Problems: Apply deep technical expertise and creativity to address novel testing challenges related to LLMs, such as ensuring the AI-generated UI flows are robust and predictable.

Were looking for a highly motivated and experienced automation engineer with a strong passion for quality and performance. If youre passionate about quality and efficiency, then join our team. You will play an important part in Harmony SASEs product development process. You will create and implement strategy for quality coordination and automation testing, as well as suggesting solutions to identified quality problems.
You will also be responsible for designing, developing, and executing performance testing strategies for our cybersecurity solutions to ensure optimal performance and scalability. You will collaborate with development teams to identify performance requirements for new features and releases, and work with them to ensure that performance issues are addressed before they impact our customers. The successful candidate will have a strong technical automation background, experience with performance testing tools and methodologies, and a passion for delivering high-quality software. If you're a self-starter who is eager to learn and take on new challenges, we encourage you to apply.
Key Responsibilities
Create and maintain automation frameworks for the R&D products
Design, automate and implement test cases for a variety of products, using the latest technologies on the market
Develop and apply integrated testing processes for new and existing products, using the latest tools and technology
Review requirements, specifications, and technical design documents to provide timely and meaningful feedback
Use different testing techniques and test-driven development strategies
Work hand-in-hand with manual QA to learn about the system and find ways to improve the automation flows
Creating testing tools to improve our QA capabilities
Build load and performance testing frameworks
Identify key KPIs for product quality
Challenge our methodologies and tools and strive to continuously improve
Monitor and analyze performance metrics to proactively identify potential issues
Experience with working and configure monitoring tools such as DataDog Grafana Etc.

We are looking for a DevOps Engineer to join our dynamic and growing team. This is an opportunity to work alongside top engineers, gain hands-on experience in production environments, and help scale secure, high-performance services used by customers around the globe. You will be part of a fast-paced, startup-like environment, with the backing and stability of a global cybersecurity leader.
Key Responsibilities
Support the deployment and maintenance of scalable, multi-tenant environments across cloud platforms
Assist in automating infrastructure using Infrastructure-as-Code tools and CI/CD pipelines
Monitor and improve the reliability, performance, and security of platform services
Collaborate with development, product, and operations teams to deliver new features and improvements
Troubleshoot infrastructure and application issues in development and production environments
Implement custom user interfaces using the latest programming techniques and technologies
Design, develop, and maintain DevOps-related microservices that support platform automation and reliability
Design and integrate agentic AI capabilities into DevOps workflows to automate decision-making, incident response, and platform operations.

we 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 - 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 Software Developer
As a Software Developer you will be responsible to:
Play a key role in designing and implementing infrastructure solutions to support our development and deployment processes.This role requires a versatile individual with strong technical skills, an out-of-the-box thinker, and a passion for solving challenging problems in cloud-based environments.
As part of the role, you will also collaborate on integrating and enabling modern AI-powered tools and services within the development ecosystem, helping teams adopt intelligent automation and emerging technologies where they add clear value.
Develop, maintain, and optimize Node.js -based services and tools for cloud platforms (AWS preferred).
Design and implement scalable and secure infrastructure solutions, leveraging modern cloud technologies.
Build and maintain APIs, microservices, and server-side applications using Node.js
Collaborate with cross-functional teams to integrate CI/CD pipelines and improve deployment efficiency.
Troubleshoot and resolve technical bottlenecks in cloud-based systems.
Contribute to system architecture design and ensure best practices are followed.
Stay up-to-date with emerging technologies and trends to continuously improve development and deployment processes.

we are looking for an experienced QA Engineer (Manual and Automation) to join the CTO department and design and execute manual and automated test plans for web and mobile 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 - where you want to be!
So what will you actually be doing?
Design, plan, analyze QA tests for web, backend and mobile applications.
Work closely with the development teams and be part of a development cycle.
Design and execute Manual automated end-to-end regression and sanity tests, identifying gaps and deficiencies.
Design and execute automated end-to-end regression and sanity tests, establish automation infrastructure, develop automated test scripts, and take on the challenge of building automation tests from scratch.
Assess delivery readiness and maintain outstanding UX/UI standards through manual testing as needed Review final product functionality before releases.
Handle software updates, patches, and bug fixes.

Join our companys AI research group, a cross-functional team of ML engineers, researchers and security experts building the next generation of AI-powered security capabilities. Our mission is to leverage large language models to understand code, configuration, and human language at scale, and to turn this understanding into security AI capabilities which will drive our company AI future security solutions.
We foster a hands-on, research-driven culture where youll work with large-scale data, modern ML infrastructure, and a global product footprint that impacts over 100,000 organizations worldwide.
Key Responsibilities
Your Impact & Responsibilities
As a Senior ML Research Engineer, you will be responsible for the end-to-end lifecycle of large language models: from data definition and curation, through training and evaluation, to providing robust models that can be consumed by product and platform teams.
Own training and fine-tuning of LLMs / seq2seq models: Design and execute training pipelines for transformer-based models (encoder-decoder, decoder-only, retrievalaugmented, etc.), and fine-tune open-source LLMs on our company-specific data (security content, logs, incidents, customer interactions).
Apply advanced LLM training techniques such as instruction tuning, preference / contrastive learning, LoRA / PEFT, continual pre-training, and domain adaptation where appropriate.
Work deeply with data: define data strategies with product, research and domain experts; build and maintain data pipelines for collecting, cleaning, de-duplicating and labeling large-scale text, code and semi-structured data; and design synthetic data generation and augmentation pipelines.
Build robust evaluation and experimentation frameworks: define offline metrics for LLM quality (task-specific accuracy, calibration, hallucination rate, safety, latency and cost); implement automated evaluation suites (benchmarks, regression tests, redteaming scenarios); and track model performance over time.
Scale training and inference: use distributed training frameworks (e.g. DeepSpeed, FSDP, tensor/pipeline parallelism) to efficiently train models on multi-GPU / multi-node clusters, and optimize inference performance and cost with techniques such as quantization, distillation and caching.
Collaborate closely with security researchers and data engineers to turn domain knowledge and threat intelligence into high-value training and evaluation data, and to expose your models through well-defined interfaces to downstream product and platform teams.