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Required SOC Quality and Reliability Engineer, Cloud
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Tel Aviv, Israel; Haifa, Israel.
About the job
In this role, youll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive TPU (Tensor Processing Unit) technology that powers our most demanding AI/ML applications. Youll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our TPU. You'll contribute to the innovation behind products loved by millions worldwide, and leverage your design and verification expertise to verify complex digital designs, with a specific focus on TPU architecture and its integration within AI/ML-driven systems.
Our data centers are the most advanced in the world. In this role, you will help build the state-of-the-art SoCs that power these data centers by driving quality and reliability processes from the Integrated Circuit perspective. You will have an opportunity to create silicon and follow it into the field and back to drive improvements for the next-generations of chips.
You will have an understanding of Integrated Circuit (IC) flows, wafer processing, testing, qualification, yield, reliability, and failure analysis is expected. You will work with various cross-functional teams to develop quality and reliability specifications, develop and deploy design guidelines, and develop and execute and test plans. You will collaborate with global hardware quality and reliability teams, silicon design, validation and engineering teams.The AI and Infrastructure team is redefining whats possible.
Responsibilities
Lead the strategic definition and development of Design-for-Reliability (DfR) guidelines, collaborating with cross-functional subject matter experts to integrate reliability into early design stages.
Establish and direct the development of qualification hardware and test methodologies, managing internal teams and external vendors to ensure silicon and package verification.
Execute comprehensive silicon and package qualification programs (including high-temperature operating life (HTOL), early life failure rate (ELFR), electrostatic discharge and latch-up (ESD/LU), and biased highly accelerated stress test (b/HAST)) and conduct in-depth failure analysis to resolve quality issues.
Analyze data from qualification programs, high-volume manufacturing, and field returns to identify failure mechanisms and trends for yield and reliability optimization.
Develop and implement physics-based statistical quality and reliability models (e.g., early life failure (ELF), time-dependent dielectric breakdown (TDDB), or negative bias temperature instability (NBTI)) to predict device failure mechanisms and lifetime behaviors.

Were building foundational infrastructure to secure AI agents-including their identities, access patterns, and interactions with sensitive systems and data.
This includes designing intelligent, dynamic mechanisms for ephemeral access control, secrets management, and agent and user identity tailored to the modern agent ecosystem.
As the Manager, youll not only help define how agents authenticate, receive scoped access, perform actions securely, and leave behind a verifiable audit trail - youll also be responsible for building and leading a high-impact engineering team from the ground up.
This is a rare opportunity to combine hands-on engineering with technical leadership-writing critical code, mentoring engineers, sharing knowledge, and driving best practices-while building a platform from the ground up at the cutting edge of AI, identity, and security.
Responsibilities
Lead the end-to-end development of a secure platform for managing AI agents identities, permissions, access control, and execution context.
Recruit, onboard, and mentor a team of engineers, shaping the teams culture and technical direction.
Drive the design and implementation of core services, ensuring high performance, security, and maintainability.
Enforce engineering excellence and best practices, including testing, code reviews, observability, secure coding, and CI/CD pipelines.
Stay hands-on: actively contribute to critical paths in architecture, prototyping, and complex problem-solving.
Ensure your teams deliverables meet high standards of performance, resilience, and security in production.

We are looking for a Platform Manager, AI Transformation to lead our strategic transition into an AI-native engineering organization. In this high-impact role, you will establish and lead the AI Platform Enablement Team, turning AI from isolated experimentation into a scalable, secure, and standardized engineering capability. You will be responsible for defining how engineers collaborate with AI agents, introducing autonomy safely, and building reusable AI foundational capabilities. This role combines technical leadership in platform engineering with AI systems thinking and organizational enablement. You will balance the speed of innovation with essential safety, security, and reliability standards. The team works in full collaboration with cross-functional engineering groups to embed AI into daily development and operations workflows. We are looking for a hands-on technical leader who can design complex systems and also get into the details when needed to turn ambiguous ideas into production-grade capabilities.
Your Impact
Own and deliver foundational capabilities including Service-Level AI Agents, AI-assisted incident management, and AI Developer Agents for PR creation and refactoring.
Manage the AI Control Plane / MCP Infrastructure, ensuring secure, auditable interfaces with clear permission boundaries.
Roll out training programs and certification frameworks to establish AI as a first-class engineering skill.
Design and implement systems with human-in-the-loop controls, auditability, and cost control standards for safety and observability.
Build and maintain mechanisms that improve AI systems using feedback loops from code reviews, incidents, and developer feedback.