Staff CAD Engineer, Silicon Design Environment, Google Cloud

🏢 Summary: Senior Performance Co-Design Engineer role focused on analyzing and optimizing LLM serving performance on custom ML accelerators. The position develops simulation, profiling, and modeling tools, partners across hardware and software teams, and informs future TPU and cloud silicon architecture decisions. 🗂️ Requirements: Bachelor’s degree in Computer Science, Electrical Engineering, Computer Engineering, related field, or equivalent practical experience, 5 years of experience in performance modeling, performance engineering, computer architecture, co-design, or systems engineering, C++ or Python programming experience 📃 Skills: C++, Python, Modeling, Architecture, Codesign, Simulation, Profiling, LLMs, TPU 🏢 Description: Minimum qualifications • Bachelor’s degree in Computer Science, Electrical Engineering, Computer Engineering, a related field, or equivalent practical experience. • 5 years of experience in performance modeling/engineering, computer architecture, co-design, or systems engineering. • Experience programming in C++ or Python. Preferred qualifications • Master's degree or PhD in Electrical Engineering, Computer Engineering, or Computer Science, with an emphasis on computer architecture. • Experience with hardware/software co-design problems, especially performance analysis and identification at the pre-silicon stage. • Experience enabling and optimizing large-scale ML models, such as LLMs and large embedding models. • Experience with ML infrastructure, profiling tools, or deep learning inference/serving optimizations. • Familiarity with accelerator architectures. Description Google Cloud’s mission is to make every business successful through AI by combining cutting-edge technology, infrastructure, and talent. AI/ML software engineers in Cloud bridge the gap between pioneering models and a massive product vehicle reaching billions. Our talent density and AI-powered tools drive rapid development, rooted in a culture of empowerment and a bias to action. The TPU Chip Architecture and Performance Co-design team is at the forefront of optimizing custom AI silicon for next-generation machine learning models. As a Senior Performance Co-Design Engineer, you will focus on conducting LLM serving studies. You will analyze and optimize the serving performance of emerging models and use cases on custom hardware, and work closely with hardware architects to influence the evolution of custom ML accelerators. The AI and Infrastructure team delivers AI and Infrastructure at scale, efficiency, reliability, and velocity. Customers include Googlers, Google Cloud customers, and billions of Google users worldwide. Teams work across software and hardware, including TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and more. Responsibilities • Conduct comprehensive serving performance studies on current and emerging LLMs, including 1P and 3P models. • Develop and maintain advanced simulation, profiling, and modeling tools to identify bottlenecks, understand key characteristics, and project serving workload performance. • Partner with model researchers and software and hardware teams to co-design architectural improvements tailored to LLM inference latency and throughput. • Drive data-backed decisions that influence the roadmap for future TPU and Cloud Silicon architectures.

🏢 Summary: Senior Chip Package SI/PI Engineer role supporting TPU-based AI/ML hardware acceleration. The position drives chip-package-system co-design, simulations, characterization, methodology development, and electrical design closure for advanced 2.5D/3D packages. 🗂️ Requirements: Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, related field, or equivalent practical experience, 10 years of chip/package or system PCB SI/PI design experience, Experience with industry SI/PI modeling toolchains, SI/PI simulation and characterization experience at package and system level, Cross-functional collaboration with chip, board, system, and vendor teams 📃 Skills: HFSS, ADS, Sigrity, Siwave, SIPI, PCB, TPU, ASIC, Python, Matlab, C++, STA, EMIR, DFM 🏢 Description: Minimum qualifications: • Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience. • 10 years of experience with SI/PI design for chip/package or system PCB. • Experience with industry Signal Integrity and Power Integrity (SI/PI) modeling toolchains, such as HFSS, ADS, Sigrity, and Siwave. Preferred qualifications: • Master’s degree or PhD in Electrical Engineering or SI/PI. • Experience in 2.5D/3D package design, including silicon interposer, silicon bridge, and 3D die stacking technologies, with SI/PI analysis expertise for high-speed interconnects. • Knowledge of next-generation memory and chiplet standards, including timing budgets and design and sign-off methodologies. • Understanding of Static Timing Analysis, on-chip DVD/EMIR, system voltage budgets, and voltage regulator modeling and design. • Ability to lead cross-functionally across chip design, physical design, STA, packaging, system, and validation teams. • Proficiency in Python, Matlab, or C++ for automation flows and advanced data processing and analysis. In this role, you will help shape AI/ML hardware acceleration and drive TPU technology for demanding AI/ML applications. You will develop custom silicon solutions and contribute design and verification expertise for complex digital designs, with a focus on TPU architecture and its integration in AI/ML-driven systems. As a Chip Package Signal Integrity/Power Integrity (SI/PI) Engineer on the chip implementation team, you will be responsible for chip-package design, SI/PI simulation, and characterization at package and system level. You will work with system architects, ASIC engineers, SI/PI engineers, chip and board design teams, system design teams, and vendors to deliver chip packaging signal and power implementations that meet chip, package, and system electrical requirements. • Drive chip-package-system co-design through SI/PI analysis and optimization, contributing to product definition and optimizing chip floorplans, power-tree structures, and netlists for HPC using 2.5D/3D package technology. • Develop power-integrity methodologies for advanced package technology and improve methodology accuracy and productivity. • Evaluate new package technologies and high-speed interface IP. • Collaborate with chip design, system design, and supplier teams to establish chip-package SI/PI targets, define chip-design boundaries, and explore SI/PI and DFM trade-offs for package design closure in production. • Provide feedback on chip floorplans based on package and system routability and SI/PI considerations.

🏢 Summary: Lead manufacturing test engineering for hardware systems, managing a team and developing scalable test strategies, automation, and process improvements. The role addresses complex product failures through RCCA, data collection, and manufacturing-process qualification for server, storage, and networking hardware. 🗂️ Requirements: Bachelor’s degree in Computer Science, Electrical Engineering, or equivalent engineering experience, 10 years of test engineering experience in electronics manufacturing, 8 years of people management experience, Python, Bash, and Shell scripting experience for product-specific test plans and test execution 📃 Skills: Python, Bash, Shell, RCCA, ICT, BSCAN 🏢 Description: Minimum qualifications • Bachelor’s degree in Computer Science, Electrical Engineering, or equivalent engineering experience. • 10 years of experience in Test Engineering in electronics manufacturing. • 8 years of experience in people management. • Experience coding in Python, Bash, and Shell scripting to generate product-specific test plans and execute testing accordingly. Preferred qualifications • Experience in manufacturing, quality, or product engineering for hardware technology and systems. • Experience working with server, storage, and networking products, especially AI and ML servers, racks, and integration. • Experience with test station bring-up, gauge R&R/correlation, and partner or agreement manufacturing (ODM, OEM, JDM). • Experience managing manufacturing test hardware using custom electronics, fixturing, instrumentation, and defining test strategy, test automation, test optimization, and scaling test capacity. • Experience with design for test and structural tests such as ICT/BSCAN, Board- and System-level Functional Tests. • Ability to drive improvement of test systems and processes for scaling test capacity. About the job Join a team developing custom silicon solutions that support direct-to-consumer hardware products. Contribute to next-generation hardware experiences focused on performance, efficiency, and integration, while supporting the technical infrastructure behind data centers, platforms, and networks. Responsibilities • Lead a team; set and communicate individual and team priorities that support organizational goals. • Meet regularly with individuals to discuss performance and development, and provide feedback and coaching. • Apply Root Cause Corrective Action (RCCA) fundamentals and collaborate with teams to analyze failures and resolve issues. • Define and execute data-collection activities for highly complex technical issues. • Drive process design, optimization, and qualification activities for manufacturing processes involving components, parts, or products.

🏢 Summary: Customer Engineer role partnering with sales teams to design and demonstrate Google Cloud solutions for customers. The position leads technical discovery, demos, pilots, solution architecture, and delivery planning to win and expand cloud workloads. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 6 years of cloud computing experience, 6 years of presentation delivery experience, Experience presenting to technical stakeholders and executive leaders 📃 Skills: Cloud, GoogleCloud, A2A, LangGraph, CrewAI, AutoGen, VertexAI, LLM, TTFT, MCP, Authentication, Quantization 🏢 Description: Minimum qualifications • Bachelor's degree or equivalent practical experience. • 6 years of experience with cloud computing and delivering presentations. • Experience engaging with, and presenting to, technical stakeholders and executive leaders. Preferred qualifications • Experience navigating AI infrastructure consumption models and optimizing high-throughput training/inference clusters. • Experience implementing multi-agent systems using frameworks such as A2A, LangGraph, CrewAI, and AutoGen. • Experience navigating the startup life cycle, from initial prototyping with AI Studio to scaling and achieving product-market fit on Vertex AI. • Experience working with, and a passion for, the high-growth startup ecosystem and its typical rapid-scaling issues. • Knowledge of LLM-native performance metrics, including TTFT, tokens/sec, and cost-per-request, and techniques for optimizing state management, quantization, and provisioned throughput. • Ability to implement secure agentic workflows incorporating MCP, tool-calling, and enterprise-grade authentication. About the job As a Customer Engineer, you will partner with technical sales teams to differentiate cloud solutions for customers. You will serve as the customer’s primary technical partner and trusted advisor, leading technical conversations to understand business issues. You will troubleshoot technical questions and roadblocks, participate in proofs of concept and demos, and architect cross-pillar cloud solutions. You will drive the technical win, define delivery and consumption plans, and present practical solutions to technical and business leaders. You will identify, pursue, and win new business workloads while expanding existing ones. The role requires broad technical expertise across infrastructure modernization, application modernization, data analytics, and related areas, combined with sales expertise, market knowledge, and direct technical engagement. Responsibilities • Develop and own the technical account plan and strategy, participating in planning and supporting targeted sales motions. • Combine sales, programming, and solutions architecture expertise to prove the value of the cloud portfolio through complex demos, pilots, and in-depth workshops. • Architect cross-pillar solutions, drive technical wins, and define initial delivery plans for customers; continue to lead technical engagement during the solution phase. • Facilitate the post-sales transition by supporting pricing activities and transitioning the final delivery plan to implementation teams. • Maintain awareness of progress against the delivery plan, providing support to cross-functional teams during ramp, delivery, migration, or implementation phases.

🏢 Summary: Lead Google Cloud AI Research engineering teams developing and deploying large-scale generative AI solutions. The role combines technical strategy, ML infrastructure optimization, system design, code development, and people leadership across multiple teams and locations. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 8+ years of software development experience, 5+ years leading ML design and ML infrastructure optimization, 3+ years in technical leadership, 2+ years with state-of-the-art GenAI techniques or related concepts, 2+ years of people management or team leadership experience 📃 Skills: Python, C, C++, Java, JavaScript, ML, GenAI, LLMs, Multimodal, Vision, Deployment, Evaluation, Debugging, Finetuning 🏢 Description: Minimum qualifications • Bachelor’s degree or equivalent practical experience. • 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript). • 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). • 3 years of experience in a technical leadership role. • 2 years of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision). • 2 years of experience in a people management or team leadership role. Preferred qualifications • Master’s degree or PhD in Engineering, Computer Science, or a related technical field. • 3 years of experience working in an organization involving cross-functional or cross-business projects. About the job Software Engineering Managers provide technical leadership for major projects while managing teams of engineers. They manage project goals, contribute to product strategy, develop their teams, and help engineers optimize their code. This role manages engineers across multiple teams and locations, a large product budget, and the deployment of large-scale projects across multiple international sites. The Google Cloud AI Research team addresses AI challenges across industries including technology, healthcare, finance, and retail, conducting research with scientific and real-world impact and collaborating with product teams to bring innovations to customers. Responsibilities • Set and communicate team priorities that support broader organizational goals; align strategy, processes, and decision-making across teams. • Set clear expectations based on individuals’ levels and roles; meet regularly to discuss performance and development, and provide feedback and coaching. • Develop the mid-term technical vision and roadmap for one or more teams; evolve the roadmap for future requirements and infrastructure needs. • Design, guide, and vet system designs; write product or system development code to solve ambiguous problems. • Lead the design of GenAI solutions, optimize ML infrastructure, and guide data preparation and model optimization strategies.

🏢 Summary: Lead a newly consolidated engineering team building the technical foundation for safe, scalable Google Cloud use across Alphabet, including AI solutions and infrastructure automation. The role combines people leadership, technical strategy, system design, and hands-on engineering for large-scale, international deployments. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 8 years of software development experience, 2 years of people management or team leadership experience, Experience integrating generative AI tools or LLM interfaces into workflows 📃 Skills: SoftwareDevelopment, GenerativeAI, LLMs, Leadership 🏢 Description: Minimum qualifications • Bachelor’s degree, or equivalent practical experience. • 8 years of experience in software development. • 2 years of experience in a people management or team leadership role. • Experience integrating generative AI tools or LLM interfaces into workflows. Preferred qualifications • Master's degree or PhD in Computer Science or a related technical field. • 3 years of experience working in a complex, matrixed organization. • Experience or strong interest in building execution runtimes and sandboxes for AI/ML workloads or autonomous agent frameworks (e.g., Jetski, CASG, Vertex Agent Engine). • Experience managing corporate customer migration, intake pipelines, or onboarding workflows at scale. • Familiarity with Google Cloud security products (such as VPC Service Controls and Cloud Firewalls), as well as advanced networking technologies like eBPF network policies, Cilium, and Envoy sidecar proxies. • Familiarity with Google-internal production primitives and data access layers (F1, Spanner). About the job Software Engineering Managers provide technical leadership for major projects while managing teams of engineers. They optimize their own code, enable engineers to optimize theirs, manage project goals, contribute to product strategy, and develop their teams. Teams work across areas including information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, and user interface design. With technical and leadership expertise, you will manage engineers across multiple teams and locations, oversee a large product budget, and lead deployment of large-scale projects across multiple international sites. The Hybrid Cloud Environment (HCE) team enables Alphabet’s safe-by-default use of Google Cloud Platform (GCP) by shifting non-functional requirements—including security, privacy, regulatory, and FinOps—into the platform layer. You will lead a newly consolidated engineering team combining the former Cloud AI Solutions and Corp Run workstreams; the team will support Cloud for Alphabet (C4A) and Project Reef, making “intent become infrastructure.” The Core team builds the technical foundation behind flagship products. The team owns and advocates for underlying design elements, developer platforms, product components, and infrastructure; builds central solutions across products; removes technical barriers; strengthens existing systems; and influences important technical decisions across the organization. Responsibilities • Set and communicate team priorities that support broader organizational goals. • Align strategy, processes, and decision-making across teams. • Set clear expectations for individuals based on their level and role, aligned with organizational goals. • Meet regularly with individuals to discuss performance and development, and provide feedback and coaching. • Develop the mid-term technical outlook and roadmap for one or more teams. • Evolve the roadmap to meet anticipated future requirements and infrastructure needs. • Design, guide, and vet system designs within the broader area, and write product or system development code to solve ambiguous problems. • Review engineers’ code and provide feedback to ensure best practices for style, code check-in, accuracy, testability, and efficiency.

🏢 Summary: Senior embedded software engineering role focused on designing, developing, testing, deploying, and maintaining large-scale infrastructure software. The position provides technical leadership for high-impact projects, aligns distributed teams, and manages delivery priorities and timelines. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 8 years of software development experience, 7 years of embedded operating systems experience, 5 years of software design, architecture, testing, and product-launch experience, Kernel programming experience, Firmware experience, C or C++ coding experience 📃 Skills: C, C++, Kernel, Firmware, Embedded, Networking, Algorithms, Architecture 🏢 Description: Minimum qualifications • Bachelor's degree or equivalent practical experience. • 8 years of experience in software development. • 7 years of experience working with embedded operating systems. • 5 years of experience with design and architecture; and testing/launching software products. • Experience in Kernel programming and firmware. • Coding experience in C or C++. Preferred qualifications • Master’s degree or PhD in Engineering, Computer Science, or a related technical field. • 8 years of experience with data structures and algorithms. • 5 years of experience in a technical leadership role leading project teams and setting technical direction. • 3 years of experience working in a complex, matrixed organization involving cross-functional or cross-business projects. • Experience with data center networking. About the job Software engineers develop next-generation technologies that support large-scale information services and products. This role works on a project critical to business needs, with opportunities to change teams and projects as priorities evolve. Engineers are expected to be versatile, demonstrate leadership, and take on new full-stack problems. Using technical expertise, you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions. The AI and Infrastructure team delivers AI and infrastructure capabilities at scale, with a focus on efficiency, reliability, and velocity. Its work spans software and hardware, including TPUs, Vertex AI for Google Cloud, global networking, data-center operations, systems research, and hyperscale computing platforms. Responsibilities • Provide technical leadership on high-impact projects. • Influence and coach a distributed team of engineers. • Facilitate alignment and clarity across teams on goals, outcomes, and timelines. • Manage project priorities, deadlines, and deliverables. • Design, develop, test, deploy, maintain, and enhance large-scale software solutions.

🏢 Summary: Software engineering role focused on building and operating large-scale technical infrastructure, distributed systems, networks, and cloud platforms. The position involves end-to-end development, design reviews, code quality, documentation, and troubleshooting of system, hardware, network, and service issues. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 2 years of programming experience in C++, Python, or Go, 2 years of experience with large-scale infrastructure, distributed systems, networks, cloud technologies, storage, or hardware architecture 📃 Skills: C++, Python, Go, Cloud, Storage, Networks, Infrastructure 🏢 Description: Minimum qualifications • Bachelor’s degree or equivalent practical experience. • 2 years of experience programming in C++, Python, or Go. • 2 years of experience developing large-scale infrastructure, distributed systems, or networks; or experience with cloud computing technologies, storage, or hardware architecture. Preferred qualifications • Master’s degree or PhD in Computer Science or a related technical field. • 2 years of experience with performance analysis, large-scale systems data analysis, visualization tools, or debugging. • 2 years of experience with data structures or algorithms in an academic or industry setting. • Experience developing accessible technologies. • Proficiency in code and system health, diagnosis and resolution, and software test engineering. About the job Software engineers develop next-generation technologies that support how billions of users connect, explore, and interact with information. Products operate at massive scale and span areas including information retrieval, distributed computing, large-scale system design, networking, data storage, security, artificial intelligence, natural language processing, UI design, and mobile development. This role is assigned to a project critical to technical infrastructure needs, with opportunities to move between teams and projects as business needs evolve. Engineers are expected to be versatile, demonstrate leadership, and take on new full-stack challenges. The Technical Infrastructure team develops and maintains data centers, platforms, and networks that support products and services. The AI and Infrastructure team delivers AI and infrastructure capabilities at scale, with work spanning hyperscale computing, TPUs, Vertex AI, global networking, data center operations, systems research, software, and hardware. Responsibilities • Write product or system development code. • Participate in or lead design reviews with peers and stakeholders to select among available technologies. • Review code from other developers and provide feedback on best practices, including style guidelines, code check-in, accuracy, testability, and efficiency. • Contribute to documentation or educational content, adapting it for product or program updates and user feedback. • Triage, debug, track, and resolve product or system issues by analyzing their sources and impacts on hardware, network, or service operations and quality.

🏢 Summary: Lead Technical Program Manager role driving the development and production delivery of next-generation AI/ML GPU systems and infrastructure solutions for cloud and technical infrastructure use cases. The individual contributor will lead cross-functional hardware and software programs, manage schedules and risks, and align technical execution across engineering, product, data center, networking, supply chain, and operations teams. 🗂️ Requirements: Bachelor’s degree in a technical field or equivalent practical experience, 5 years of program management experience, Experience launching new products across hardware, software, and systems infrastructure, Experience with data center infrastructure and deployment 📃 Skills: Programmanagement, Hardware, Software, Infrastructure, Datacenters, GPU, IaaS, VM, Baremetal, Distributedsystems 🏢 Description: Minimum Qualifications • Bachelor's degree in a technical field, or equivalent practical experience. • 5 years of experience in program management. • Experience in launching new products (NPI), encompassing hardware and software development, and systems infrastructure. • Experience with data center infrastructure and deployment. Preferred Qualifications • 5 years of experience managing cross-functional or cross-team projects. • Experience in hardware engineering, software engineering, GPU systems, and solutions. • Experience launching IaaS VM, bare metal, and machine-of-the-day products. • Ability to assess engineering problems and understand large-scale distributed systems. About the Job As a Technical Program Manager, you will use technical expertise to lead complex, multidisciplinary projects from start to finish. You will work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate with cross-functional partners. You will explain analyses and recommendations to executives and discuss technical tradeoffs in product development with engineers. The Platforms Infrastructure Engineering Program Management Office partners with compute engineering, networking, data center, supply chain, and operations teams to deliver AI/ML and standard compute systems and solutions supporting cloud IaaS and technical infrastructure services. This individual contributor role serves as the lead Technical Program Manager driving system and solution development for next-generation AI/ML GPU systems for cloud and technical infrastructure use cases. Responsibilities • Lead a cross-functional team across organizational levels and functional areas to develop and deliver hardware programs from inception to production. • Set program vision and direction by defining goals and objectives, evaluating and supervising multiple projects, organizing cross-project work, and establishing program controls, governance, and standards. • Use technical judgment to drive project delivery, conduct technology reviews, challenge proposals, build consensus, and align cloud and central processes. • Develop project documentation, process maps, presentations, and tracking reports that provide detailed project status. • Engage with engineering directors, product leaders, and Technical Program Manager groups to streamline processes, simplify execution, manage OKRs, support on-time releases, introduce efficiency tooling, and help teams execute.

🏢 Summary: Lead the architecture and scaling of AI/ML infrastructure for YouTube Ads creative automation. The role focuses on high-throughput distributed systems, GenAI media-processing pipelines, experimentation platforms, and technical leadership across product and research teams. 🗂️ Requirements: Bachelor’s degree in Computer Science, related technical field, or equivalent practical experience, 8 years of software development experience, 5 years of software product testing and launch experience, 5 years building large-scale infrastructure, distributed systems, networks, compute, storage, or hardware architecture, 3 years of software design and architecture experience, Experience designing or deploying machine-learning infrastructure or platforms 📃 Skills: Python, TensorFlow, PyTorch, Cloud, Distributed, Infrastructure, Architecture, Algorithms, MachineLearning, DeepLearning, GenAI 🏢 Description: Minimum qualifications • Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience. • 8 years of experience in software development. • 5 years of experience testing and launching software products. • 5 years of experience building and developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture. • 3 years of experience with software design and architecture. • Experience designing or deploying machine learning (ML) infrastructure or platforms. Preferred qualifications • Master’s degree or PhD in Engineering, Computer Science, or a related technical field. • 8 years of experience with data structures and algorithms. • 3 years of experience in a technical leadership role leading project teams and setting technical direction. • 3 years of experience working in a complex, matrixed organization involving cross-functional or cross-business projects. • Proficiency in deep learning frameworks (e.g., TensorFlow, PyTorch) and cloud/distributed data technologies. About the job Develop next-generation technologies that operate at massive scale. Work on a project critical to business needs, with opportunities to switch teams and projects as priorities evolve. Bring ideas across areas including distributed computing, large-scale system design, networking, data storage, artificial intelligence, and more. Manage project priorities, deadlines, and deliverables. Design, develop, test, deploy, maintain, and enhance software solutions. The YouTube Ads Creative Optimization (YACO) team develops Creative Automation applications that drive advertiser value with minimal advertiser effort by leveraging AI technologies. The team operates at the intersection of Ads, YouTube, and Research. Responsibilities • Serve as the technical leader responsible for architecting, scaling, and steering next-generation infrastructure that powers AI/ML applications. • Operate at the intersection of Ads, YouTube, and GenAI research to build high-throughput systems enabling seamless creative generation and optimization. • Define the technical roadmap and architect scalable foundational infrastructure, including creative data engines, generation and rendering pipelines, and agentic orchestration frameworks. • Design and optimize distributed systems for complex GenAI and heavy media-processing workloads. • Build and mature experiment and learning infrastructure to accelerate model training, evaluation, and rapid deployment. • Partner with Product Management, Research, and executive leadership to align infrastructure capabilities with long-term business goals. • Guide, mentor, and elevate executive and junior engineers, fostering technical excellence and execution.