Google94 followers

Deployment Lead, AI Infrastructure, Google Cloud

SeniorFull-timeHybridSydney NSW, AustraliaPosted 1 week agoVerified 1 week ago
Pending fitX of Y criteria met

About the job

This job is about leading the deployment of advanced accelerated computing systems within the Google Enterprise Services team. By bridging the gap between specialized hardware and enterprise software, you will shape the future of large-scale distributed computing for major organizations. Collaboration and innovation are at the heart of how the team operates, ensuring that every project is a step towards digital transformation.

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You'll be responsible for

✅

Managing successful implementations

Work with customer technical leads, client executives, and partners to manage and deliver successful implementations of cloud solutions, becoming a trusted advisor to decision makers throughout the engagement.
🏗️

Proposing solution architectures

Propose solution architectures and manage the deployment of cloud-based distributed virtualized infrastructure solutions according to complex customer requirements and implementation best practices.
🤝

Collaborating with internal teams

Work with internal specialists, Product, and Engineering teams to package approaches, best practices, and lessons learned into thought leadership, methodologies, and published assets.

Key criteria

🎓

Bachelor’s degree or equivalent

Required educational background for technical expertise.

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🛠️

10+ years troubleshooting experience

Proven experience resolving technical issues for partners or customers.

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🤝

7+ years in customer management

Demonstrated experience engaging stakeholders for successful deployments.

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5 criteria for this job
Bachelor’s degree or equivalent
Required educational background for technical expertise.

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10+ years troubleshooting experience
Proven experience resolving technical issues for partners or customers.

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7+ years in customer management
Demonstrated experience engaging stakeholders for successful deployments.

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5+ years with AI/ML infrastructure
Experience with technologies like GPUs and Kubernetes is essential.

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Programming experience
Experience reading code in languages like Java, C++, or Python.

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