We are seeking a System QA Automation Engineer to drive the validation of our high-performance distributed storage platform, designed for massive AI workloads. In this role, you will architect automation frameworks and tests from the ground up, ensuring seamless integration with the worlds leading orchestration platforms (Kubernetes, OpenShift, OpenStack, Terraform, and vSphere). You will be responsible for defining test strategies, building Python-based tools, and certifying our NFS drivers across a complex matrix of Linux environments.
Key Responsibilities:
Design, develop, and test complex distributed storage products from scratch using Python to interface with storage controllers and orchestration APIs.
Validate storage provisioning, management, and performance within Kubernetes, OpenShift, OpenStack (Cinder/Manila), and VMware vSphere environments.
Lead the testing and certification of NFS drivers (v3/v4) on diverse client operating systems (various Linux distros, Windows Server).

We are looking for a Quality CI Enigneer to join our growing team!
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
Key Responsibilities
Daily Analysis of automation CI results, Develop, refactor and design automation tests and pipelines integrating with SW tools from the ground up, interfacing to various systems and tests (Python-based).
Work closely with developers to create and maintain a state of the art system tests.
Define, develop and execute automated testing plans with deep system knowledge and understanding.

We are looking for a QA Automation Engineer to join our growing team!
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
Key Responsibilities
Develop Testing & Automation SW tools from the ground up, interfacing to various systems and tests (Python-based).
Work closely with developers to create and maintain a state of the art system tests
Define, develop and execute testing plans with deep system knowledge and understanding.

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.

This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
We are seeking an experienced Solutions Data Engineer who possess both technical depth and strong interpersonal skills to partner with internal and external teams to develop scalable, flexible, and cutting-edge solutions. Solutions Engineers collaborate with operations and business development to help craft solutions to meet customer business problems.
A Solutions Engineer works to balance various aspects of the project, from safety to design. Additionally, a Solutions Engineer researches advanced technology regarding best practices in the field and seek to find cost-effective solutions.
Job Description:
Were looking for a Solutions Engineer with deep experience in Big Data technologies, real-time data pipelines, and scalable infrastructure-someone whos been delivering critical systems under pressure, and knows what it takes to bring complex data architectures to life. This isnt just about checking boxes on tech stacks-its about solving real-world data problems, collaborating with smart people, and building robust, future-proof solutions.
In this role, youll partner closely with engineering, product, and customers to design and deliver high-impact systems that move, transform, and serve data at scale. Youll help customers architect pipelines that are not only performant and cost-efficient but also easy to operate and evolve.
We want someone whos comfortable switching hats between low-level debugging, high-level architecture, and communicating clearly with stakeholders of all technical levels.
Key Responsibilities:
Build distributed data pipelines using technologies like Kafka, Spark (batch & streaming), Python, Trino, Airflow, and S3-compatible data lakes-designed for scale, modularity, and seamless integration across real-time and batch workloads.
Design, deploy, and troubleshoot hybrid cloud/on-prem environments using Terraform, Docker, Kubernetes, and CI/CD automation tools.
Implement event-driven and serverless workflows with precise control over latency, throughput, and fault tolerance trade-offs.
Create technical guides, architecture docs, and demo pipelines to support onboarding, evangelize best practices, and accelerate adoption across engineering, product, and customer-facing teams.
Integrate data validation, observability tools, and governance directly into the pipeline lifecycle.
Own end-to-end platform lifecycle: ingestion → transformation → storage (Parquet/ORC on S3) → compute layer (Trino/Spark).
Benchmark and tune storage backends (S3/NFS/SMB) and compute layers for throughput, latency, and scalability using production datasets.
Work cross-functionally with R&D to push performance limits across interactive, streaming, and ML-ready analytics workloads.

We are looking for a QA Automation Engineer to join our engineering team and take ownership of backend and data-focused test automation.
This role is centered on validating complex backend services, data flows, and cloud-based systems, with understanding of full end-to-end flow (including frontend).
You will design and maintain scalable automated test suites that ensure backend functionality, data accuracy, system reliability, and high-quality releases in a distributed, cloud-native environment. The role requires strong technical skills, independence, and close collaboration with backend developers, data engineers, and product managers.
Your ownership will include:
Take an active part in the entire software development lifecycle, with a strong focus on backend and data-related components.
Design, develop, and maintain automated tests for backend services, APIs, and data pipelines.
Validate data integrity and business logic across multiple data sources and environments.
Build and maintain test plans, test scripts, and test data to support reliable, production-ready releases.
Continuously improve automation infrastructure and CI/CD pipelines.
Ensure strong automated test coverage for backend and data features.
Perform root cause analysis of issues found in automation and communicate findings clearly.
Work closely with Backend, Data Engineering, and Product teams to review requirements and define effective automation strategies.
Troubleshoot technical challenges independently and propose practical, scalable solutions.
Stay up to date with backend and data automation best practices, tools, and industry trends.

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 Orcas 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.

We are seeking a skilled and motivated DevOps engineer with deep familiarity in the streaming ecosystem to join our elite infrastructure team. If you're excited by the challenge of operating mission-critical systems at scale and optimizing the developer experience through automation and tooling, wed love to hear from you.
What you will do
Automate Deployment and Operation
Oversee deployment of Kafka and RabbitMQ clusters (including Confluent Cloud & CFK). Build automation pipelines to ensure repeatability and resiliency across environments.
Monitor and Support Production Systems
Own production stability of global Kafka clusters. Handle on-call rotations, incident management, troubleshooting, and scaling challenges.
Improve Infrastructure Observability
Build and maintain observability systems: dashboards, alerting pipelines, metrics collection (Prometheus, Grafana, etc.).
Optimize System Performance
Collaborate with peers on benchmarking and optimization initiatives. Work on tuning Kafka brokers, cluster configurations, and runtime parameters.
Provide Developer Support and Training (Infra-focused)
Help developers configure topics, quotas, and consumers appropriately. Train service owners to interpret monitoring data and avoid pitfalls.
Develop and Maintain Infrastructure
Contribute to building infrastructure tools and scripts (IaC, Helm charts, etc.) that make provisioning and managing clusters reliable and efficient.
Secure Infrastructure Access
Configure and maintain secure access patterns across streaming infrastructure, ensuring proper authentication and role-based access controls are enforced for both developers and services.

Required Senior Release Engineer Infrastructure
Realize your potential by joining the leading performance-driven advertising company!
As a Senior Release Engineer on the Infrastructure group, youll play a vital role in solving scaling challenges in our build system, handling 8 million lines of code and 160,000 unit tests efficiently.
How youll make an impact:
As a Senior Release Engineer, youll bring value by:
Solve scaling challenges in our build system, handling 8 million lines of code and 160,000 unit tests efficiently.
Drive best practices for DevOps, site reliability, and infrastructure scalability.
Build and support a self-service toolset to empower developers and streamline release processes.
Design, implement, and maintain CI/CD pipelines to ensure smooth, automated, and reliable software releases.
Develop scalable infrastructure as code (IaC) solutions to improve deployment efficiency and system reliability.
Enhance observability, monitoring, and logging to proactively detect and resolve performance issues.
Work closely with development to optimize release workflows and reduce downtime.
Manage and improve containerization strategies using Kubernetes, Docker, and related technologies.
Leverage Gen-AI tools to accelerate development velocity across all RnD.
Own the management of third-party libraries in our central Java code repository, ensuring seamless Spring and Java upgrades
Our Tech Stack:
Java, Spark, Kafka, Hadoop, Cassandra, Vertica, MySQL, HDFS, BigQuery, Docker, Linux, Kubernetes, Prometheus, Metrictank, Grafana, Airflow, Redis.