Engineering Product Manager – Ai Canvas jobs at Cisco in United States, San Jose
Cisco Principal AI Infrastructure Abstraction Engineer United States, California, San Jose
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Your Impact
As an
AI Infrastructure Abstraction Engineer, you will help shape the next generation of AI compute platforms by designing systems that abstract away hardware complexity and expose logical, scalable, and secure interfaces for AI workloads. Your work will enable multi-tenancy, resource isolation, and dynamic scheduling of GPUs and accelerators at scale — making infrastructure programmable, elastic, and developer-friendly.
You will bridge the gap between raw compute resources and AI/ML frameworks, allowing infrastructure teams and model developers to consume shared GPU resources with the performance and reliability of bare metal, but with the flexibility of cloud-native systems. Your contributions will empower internal and external users to run AI workloads securely, efficiently, and predictably — regardless of the underlying hardware topology.
This role is critical to enabling AI infrastructure that is multi-tenant by design, scalable in practice, and abstracted for portability across diverse platforms.
KEY RESPONSIBILITIES
- Design and implement infrastructure abstractions that cleanly separate logical compute units (vGPUs, GPU pods, AI queues) from physical hardware (nodes, devices, interconnects) .
- Develop runtime services, APIs, and control planes to expose GPU and accelerator resources to users and frameworks with multi-tenant isolation and QoS guarantees .
- Architect systems for secure GPU sharing , including time-slicing, memory partitioning, and namespace isolation across tenants or jobs.
- Collaborate with platform, orchestration, and scheduling teams to map logical resources to physical devices based on utilization, priority, and topology.
- Define and enforce resource usage policies , including fair sharing, quota management, and oversubscription strategies.
- Integrate with model training and serving frameworks (e.g., PyTorch, TensorFlow, Triton) to ensure smooth and predictable resource consumption.
- Build observability and telemetry pipelines to trace logical-to-physical mappings, usage patterns, and performance anomalies.
- Partner with infrastructure security teams to ensure secure onboarding, access control, and workload isolation in shared environments.
- Support internal developers in adopting abstraction APIs, ensuring high performance while abstracting away low-level details.
- Contribute to the evolution of internal compute platform architecture, with a focus on abstraction, modularity, and scalability.
Minimum Qualifications:
- Bachelors + 15 years of related experience, or Masters + 12 years of related experience, or PhD + 8 years of related experience
- Experience building scalable, production-grade infrastructure components or control planes using Go, Python, and C++ ,
- Experience with Kubernetes, Docker or Kubevirt for v irtualization, containerization , and orchestration frameworks
- Experience designing or implementing logical resource abstractions for compute, storage, or networking with a focus in multi-tenant environments .
- Experience integrating with AI/ML platforms or pipelines (e.g., PyTorch, TensorFlow, Triton Inference Server, MLFlow).
Preferred Qualifications:
- Experience with GPU sharing, scheduling, or isolation techniques (e.g., MPS, MIG, time-slicing, device plugin frameworks, or vGPU technologies).
- Solid grasp of resource management concepts including quotas, fairness, prioritization, and elasticity.
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Cisco Principal Technical Product Manager AI United States, California, San Jose
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- Provide expert guidance and thought leadership within and outside the organization, shaping the development of multi-year product strategies.
- Own the end-to-end lifecycle of networking products, from ideation and requirements gathering to launch and ongoing iteration, with a focus on hyperscaler environments.
- Proactively identify and address product risks and challenges, ensuring seamless integration of hyperscaler technologies into product offerings.
- Define, analyze, and prioritize network-related product features, using data-driven insights to guide decision-making and maximize impact in AI-driven networking.
- Facilitate effective communication and collaboration among Sales, Engineering, Product Management, and Release Management to ensure alignment on product vision and execution.
- Continuously refine product management practices, tools, and processes to drive efficiency and effectiveness in delivering networking and hyperscaler-based products.
- Bachelor's degree in Computer Science, Engineering, or a related field, with 10+ years of experience in networking, cloud deployment, or software development, including 6+ years in Technical Product Management Management.
- 3+ years of experience managing products that involve cross-functional or cross-team collaboration with sales teams and end customers.
- Experience with AI/ML in a Data Center or Hyperscaler environment.
- Experience in Data Center Network Architecture, Cloud Development, Software Testing, and Deployment processes.
- Product experience within networking technologies including NPUs, Optics, NICs and switches.
- Recognized as an internal technical expert and has broad knowledge across fields of specialization
- Expertise in Data Center Network Architecture, emphasizing hyperscaler environments
- Proficiency with AI configurations
- Solid background in networking protocols, server architecture, and storage systems
- Demonstrable ability to enhance networking team productivity and streamline processes related to hyperscalers and AI
- Excellent written, presentation, and verbal communication skills tailored to networking initiatives
- Proven track record in driving quality initiatives with a solid understanding of key networking metrics
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Cisco Thermal Engineering Technical Leader United States, California, San Jose
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Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received.
Your ImpactYou will be part of a world class Component Quality and Technology Group and contribute to developing, road mapping and implementing advanced thermal solutions for Cisco’s products. You will Investigate and develop innovative thermal cooling solutions for hardware systems in large scale. You will lead in the development of test plans and qualification requirements to ensure mechanical and manufacturing robustness of thermal cooling solutions (pumps, heat pipes, vapor chambers, heat sinks, cold plates etc.). You will Engage with external vendors including ODM and component vendors on design, test and production. You will Establish parameters for thermal design/testing, correlation of design/test results to model predictions. You will Collaborate with Cisco hardware design teams to develop roadmaps and risk analyses for future thermal solutions for ASIC/IC, Optics, Power and other components and systems. You will partner with several Cisco hardware design teams to improve specifications and qualification procedures.
Minimum Qualifications:- BS in Mechanical or Chemical Engineering
- 8 – 10 years of experience in design, simulation and testing of thermal solutions for electronic devices and systems
- 8+ years of experience in electronic device and system level air cooling technologies
- Experience in mechanical design validation and testing for electronic assemblies
- Knowledge of integrated circuit packaging technologies (BGA, large body size Flip Chip BGA, 2.5D and 3D Packaging)
- Component and system reliability analysis
- 10+ years of relevant industry experience in microelectronics cooling
- Experience in developing liquid cooling solutions for electronic devices and systems.
- Experience with Thermal Interface Material Thermal Conductivity Testing procedures
- Experience with troubleshooting and thermal validation with data acquisition systems, airflow and environmental chambers
- Experience with liquid cooling (cold plates, CDUs, manifolds, piping, characterization, pumps etc.) and high-power air-cooling solutions, such as heat pipes, VCs, and 3D VCs.
- Ability to lead by influence without direct reporting chain and advise executive decision makers
- Self-starter, proven ability to work independently on multiple projects and priorities
- Excellent communication, project management and metrics design skills
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Cisco Product Manager – Secure AI Factory / Defense United States, California, San Jose
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The application window is expected to close on August 29, 2025.
NOTE: Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received.
Ultimately, we
Your Impact
As a Product Leader for AI Defense - Secure AI Factory within our AI Software & Platform team, you will lead efforts related to the following:
market opportunities and drive the strategy for securing AI applications acrosshybrid cloud environments.
Collaborate with engineering and product teams from Security, Data Center, Internet & Cloud Infrastructure to deliver features and improvements to Cisco’s Secure AI Factory solution.
Define new product capabilities for monitoring, and deploying software across distributed and hybrid environments, including on-premises and containerized platforms.
Drive prioritization of hardware, networking, and software requirements to ensure the delivery and operation of AI Defense software across hybrid (on-premiseand cloud) environments.
Lead cross-functional efforts across sales, marketing, partners, and business development teams, ensuring comprehensive enablement to drive successful adoption.
Minimum Qualifications
10+ years of relevant engineering and/or product management experience, including 5 years of recent experience
Background in cybersecurity or AI/ML platforms, or networking, or data center infrastructure, with an interestinaddressing challenges and delivering customer-centric solutions.
Familiarity with AI infrastructure solutions and architectures, encompassing high-performance compute.
Computer Science, Engineering, or equivalent degree, with a focus on applying technicalexpertiseto drive innovation and security in AI.
Preferred Qualifications
Experience with AIOps practices or AI Observability including model deployment, monitoring, and infrastructure automation. Understanding of distributed systems and cloud architectures relevant to AI/ML workloads
Excellent communication, leadership, and critical thinking skills, enabling effective partner engagement and decision-making in high-stakes environments.
Familiarity with containerization and orchestration technologies such as Kubernetes, OpenShift, Docker, or similar platforms
revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond.been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint. Simply put – we power the future.
see that the opportunities to grow and build are limitless.
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Cisco Internal Audit Manager United States, California, San Jose
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Cisco Sr Engineering Manager Infrastructure Manageability United States, California, San Jose
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The application window is expected to close on: 8/28/2025.
NOTE: Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received.
- Mentoring and developing engineering talent, fostering a culture of continuous learning and professional growth within the SONiC Group.
- Providing expert technical guidance on infrastructure, manageability, and distributed systems design and implementation.
- Leading architecture discussions, conducting code reviews, and guiding team members to deliver high-quality solutions.
- Owning project deliverables, managing schedules, and tracking progress to ensure timely execution.
- Collaborating closely with cross-functional teams, including development, product management, and security.
- Embodying and promoting Cisco’s culture and values as a role model.
- Bachelor’s degree in a STEM field.
- 10+ years of experience in embedded software development using C, C++, Go, and/or Python.
- 10+ years of experience with Linux or infrastructure software (such as gNMI, in-memory databases).
- 7+ years of experience designing and implementing distributed systems.
- 4+ years of experience in a leadership role within an engineering team.
- Experience with network operating systems in the Linux user space (e.g., SONiC).
- Proficiency with modern development tools such as GIT, Jira, Jenkins, and other CI/CD pipeline tools.
- Familiarity with virtualization and containerization technologies (e.g., KVM/Qemu, Docker, Kubernetes).
- Strong skills in performance tuning and optimization.
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Cisco AI Products Partnership Lead United States, California, San Jose
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The application window is expected to close on 9/26/25.
However, the job posting may be removed earlier if the position is filled or if a sufficient number of applications are received.
This position requires that you work in a hybrid model and you are within commuting distance to the San Francisco, CA and San Jose, CA offices. Days per week in the office are flexible.
Your Impact
As the Business Development Manager - AI Partnerships, you will play a pivotal role in building, maintaining, and advancing Cisco’s presence in the AI ecosystem. You’ll build and maintain strategic partnerships, identify growth opportunities, and align Cisco’s strengths with the needs of the AI landscape. Your work will directly contribute to the development of innovative solutions that address emerging market demands in an evolving space.
- Collaborate with product groups to align AI partnership strategies with Cisco’s core strengths and develop and execute partner support plans for innovation, enablement, marketing, and co-selling.
- Provide insights into emerging AI and market trends, articulate Cisco’s positioning within the ecosystem, and develop creative solutions for localized initiatives.
- Identifying, evaluating and supporting AI-focused partnership opportunities with key players in the industry, including startups, Hyperscalers, semiconductors and ecosystem partners.
- Build and nurture relationships with technical and business partners across the AI ecosystem while working cross-functionally with Cisco’s product, engineering, sales, marketing, and legal teams to ensure successful partnership outcomes.
- Manage all aspects of the program, including governance, business planning, return on investment analysis, and metrics reporting, while identifying areas for enhancement and implementing solutions to accelerate growth.
- 5+ years experience in a Product Management, Technical Marketing or Partnerships role.
- Demonstrated experience in analyzing market data and sales metrics to support strategic decision-making.
- Experience in driving partnerships and leading go-to-market initiatives for dynamic, high-performing companies OR
- Experience in the areas of either cloud infrastructure, semiconductors, or Artificial Intelligence/Machine Learning OR
- Experience handling the end-to-end product lifecycle for consumer or enterprise offerings.
- Strong communication, interpersonal, and problem-solving skills with a strategic approach, demonstrating the ability to influence senior executives and lead solution sales across matrixed teams.
- Experience thriving in an ambiguous, fast-paced, dynamic environment.
- Ability to navigate cross-functional teams to achieve goals.
- Demonstrate adaptability and comfort with ambiguity in a rapidly evolving industry while driving strategic business plan development and delivering measured outcomes.
- A passion for AI-driven innovation with a strong interest in the AI landscape, including trends, technologies, and key players, striving to shape the future of technology.
- A broad understanding of Cisco’s products, services, and partner community to accelerate joint sales activities with strategic partners.
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Share
Your Impact
As an
AI Infrastructure Abstraction Engineer, you will help shape the next generation of AI compute platforms by designing systems that abstract away hardware complexity and expose logical, scalable, and secure interfaces for AI workloads. Your work will enable multi-tenancy, resource isolation, and dynamic scheduling of GPUs and accelerators at scale — making infrastructure programmable, elastic, and developer-friendly.
You will bridge the gap between raw compute resources and AI/ML frameworks, allowing infrastructure teams and model developers to consume shared GPU resources with the performance and reliability of bare metal, but with the flexibility of cloud-native systems. Your contributions will empower internal and external users to run AI workloads securely, efficiently, and predictably — regardless of the underlying hardware topology.
This role is critical to enabling AI infrastructure that is multi-tenant by design, scalable in practice, and abstracted for portability across diverse platforms.
KEY RESPONSIBILITIES
- Design and implement infrastructure abstractions that cleanly separate logical compute units (vGPUs, GPU pods, AI queues) from physical hardware (nodes, devices, interconnects) .
- Develop runtime services, APIs, and control planes to expose GPU and accelerator resources to users and frameworks with multi-tenant isolation and QoS guarantees .
- Architect systems for secure GPU sharing , including time-slicing, memory partitioning, and namespace isolation across tenants or jobs.
- Collaborate with platform, orchestration, and scheduling teams to map logical resources to physical devices based on utilization, priority, and topology.
- Define and enforce resource usage policies , including fair sharing, quota management, and oversubscription strategies.
- Integrate with model training and serving frameworks (e.g., PyTorch, TensorFlow, Triton) to ensure smooth and predictable resource consumption.
- Build observability and telemetry pipelines to trace logical-to-physical mappings, usage patterns, and performance anomalies.
- Partner with infrastructure security teams to ensure secure onboarding, access control, and workload isolation in shared environments.
- Support internal developers in adopting abstraction APIs, ensuring high performance while abstracting away low-level details.
- Contribute to the evolution of internal compute platform architecture, with a focus on abstraction, modularity, and scalability.
Minimum Qualifications:
- Bachelors + 15 years of related experience, or Masters + 12 years of related experience, or PhD + 8 years of related experience
- Experience building scalable, production-grade infrastructure components or control planes using Go, Python, and C++ ,
- Experience with Kubernetes, Docker or Kubevirt for v irtualization, containerization , and orchestration frameworks
- Experience designing or implementing logical resource abstractions for compute, storage, or networking with a focus in multi-tenant environments .
- Experience integrating with AI/ML platforms or pipelines (e.g., PyTorch, TensorFlow, Triton Inference Server, MLFlow).
Preferred Qualifications:
- Experience with GPU sharing, scheduling, or isolation techniques (e.g., MPS, MIG, time-slicing, device plugin frameworks, or vGPU technologies).
- Solid grasp of resource management concepts including quotas, fairness, prioritization, and elasticity.
These jobs might be a good fit
