We are looking for Software Automation Engineer to help us develop a semiconductor platform based on a revolutionary architecture.

Take part in the development of products within a disruptive system architecture. Youll have the opportunity to work in a dynamic, open, fast-paced environment, developing the technologies that power the worlds largest cloud provider. AWS provides a highly reliable, scalable, low-cost infrastructure platform in the cloud, which powers hundreds of thousands of businesses in 190 countries around the world.

Key job responsibilities
As Software Automation Engineer, you'll be responsible for creating ML (Machine learning) and HPC (High performance computing) automation and tools, create CI/CD flows and implement effective dashboards with high scale.

Our System Product Engineering team is looking for a QA Engineer to join us and help validate the software infrastructure used by multiple teams across the organizations. This role focuses on testing internal tools, backend services, workflows, automation, and the systems that support our validation processes. You will work closely with developers, infra teams, and validation engineers to ensure that our internal software is stable, reliable, and easy to use. You will contribute to building robust test coverage, improving automation, analyzing logs and test results, and driving quality throughout the development cycle.

What youll be doing:

Plan, execute, and analyze functional, integration, and regression tests for internal infrastructure software.

Develop and maintain automated test cases and test flows.

Validate backend services, data pipelines, web tools, and internal workflows.

Investigate failures, collect logs, reproduce issues, and work with developers to identify root causes.

Review and validate new features before release, ensuring they meet quality and usability expectations.

Support CI/CD flows by monitoring automated tests and contributing to improvements.

Document test scenarios, edge cases, and validation coverage.

Provide continuous feedback to developers and infra teams to improve quality and reliability.

We are seeking an experienced QA Specialist to join our ITPE (Interconnect Product Engineering) Test/Software Development team. This position will be part of our growing team, which develops testing frameworks, core test infrastructure, and engineering tools for optical transceivers and next-generation interconnect our products. We develop a collaborative and inclusive work environment, where ideas are shared and innovation is encouraged. As a Senior QA Specialist in this group, you will own the quality of the frameworks, core libraries, and tools our developers build, ensuring they are stable, reliable, and production ready. The ideal candidate should bring a robust understanding of the SW development lifecycle and the QA role within it.

What youll be doing:
Define and own QA strategy, test plans, and quality standards for testing platforms, essential libraries, and utilities.
Build and maintain automated test pipelines; integrate quality gates into CI/CD workflows.
Maintain regression suites that catch breakages as frameworks evolve.
Develop test fixtures, mocks, and simulators for testing code in isolation.
Track quality metrics and generate summary reports of testing activities.
Collaborate with teams across ITPE including NPI, MP, data intelligence, and R&D.

We are looking for a talented software engineer with a passion for security to help build innovative edge-to-cloud security solutions for our next-generation devices and platforms.

You will contribute to and lead the development of core product features, from understanding system and product requirements and defining feature behavior, through architecture, design, and implementation, to delivering high-quality, secure services and endpoint components.

You will work across the stack, spanning firmware, hardware, operating systems, and cloud-connected security solutions, helping build the trusted security foundations of next-generation devices. You will collaborate with silicon partners, security experts, and engineering teams across us to deliver innovative, end-to-end security capabilities. The role offers significant technical ownership, opportunities to drive innovation, and continuous growth at every stage of your career.

AI is a core part of how we engineer. Our team has broad access to advanced AI capabilities, including unrestricted usage with no token limits, enabling engineers to fully integrate AI into their daily workflow. We actively use AI to accelerate design, coding, debugging, security research, testing, and documentation. We also empower engineers to go beyond personal productivity by building AI-powered tools and agents that improve how the entire team works and delivers value.

Join us in pushing the boundaries of security engineering. From silicon and firmware to operating systems and cloud-connected services, you'll help build trusted foundations that secure our future devices and experiences on a global scale.


Responsibilities

Partner with product, system, cloud, firmware, hardware, and security engineering teams to design and deliver innovative security solutions.

Contribute to and lead the design, implementation, integration, testing, and delivery of core security features spanning firmware, operating systems, endpoint software, and cloud-connected services.

Develop and integrate secure, reliable, scalable, and maintainable software and services using industry best practices and our high security and engineering standards.

Apply secure engineering practices, including threat modeling, secure design reviews, code reviews, mitigation planning, vulnerability response, and security validation.

Define technical requirements, architecture, dependencies, engineering priorities, and delivery plans in a complex cross-team environment.

Work closely with hardware, firmware, operating system, Windows internals, cloud, and security engineers to characterize solutions, define interfaces, and optimize security, reliability, and performance.

Drive features from inception through production, including quality, observability, deployment, monitoring, incident readiness, and continuous improvement.

Leverage advanced AI capabilities to accelerate engineering workflows and build AI-powered tools and agents that improve team productivity and product quality.

Continuously learn emerging security technologies and attack techniques, share knowledge with the team, and mentor peers as your experience grows.

The WSSI (Windows Silicon System Integration) team is looking for an experienced Data Science Manager to lead a team developing production-oriented AI solutions across computer vision and efficient small language models, helping bring advanced models to Windows products under real-world edge-device constraints.

This role offers a meaningful leadership opportunity: managing a diverse team that includes researchers, MLOps engineers, and data management experts, while shaping the teams technical direction and influencing product directions in close partnership with product and system engineering teams, all within a culture that values inclusion, collaboration, continuous learning, and individual growth.

The teams primary focus is developing state-of-the-art computer vision solutions that can run efficiently under real-world edge-device constraints, including model size, latency, power, and deployment efficiency. In parallel, the team explores similar optimization opportunities for SLMs, enabling advanced AI models to run more efficiently across Windows products.

In this role, you will help turn applied research into production-quality AI experiences, collaborate closely with product, system engineering, software, and silicon teams, and create impact for millions of customers.

Responsibilities

Lead, grow, and develop a diverse data science team that includes researchers, MLOps engineers, and data management experts, while fostering a culture of technical excellence, collaboration, ownership, and continuous learning.

Define and drive the teams technical roadmap in close partnership with product and system engineering teams.

Guide the development of production-oriented AI solutions from research exploration through production deployment, with a strong focus on quality, scalability, reliability, and measurable customer impact.

Drive model efficiency and deployment readiness for constrained environments, ensuring AI solutions meet real-world requirements for performance, latency, footprint, and resource usage.

Mentor team members, create clarity, set priorities, and help the team deliver high-impact results in a dynamic and evolving environment.