Senior Cloud Platform Engineer Jobs in Austin, TX
Senior Cloud Platform Engineer jobs in Austin, Texas cluster in the Domain, downtown's Congress Avenue corridor, and the East Austin tech district, with strong demand from enterprise software, semiconductor, fintech, and hyperscaler tenants. Employers hiring right now include Google, PEAK6, and Emerson. Find a role that fits below and apply directly.
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Showing 5 of 32+ Senior Cloud Platform Engineer jobs
- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Austin, TX, USA; Kirkland, WA, USA.
Minimum qualifications:
- Bachelor's degree in Computer Science, Management Information Systems, or other technical field, or equivalent practical experience.
- 4 years of debug or validation experience with CPU, dGPU, or TPU.
- 4 years of experience with technical infrastructure (deployment, maintenance, and troubleshooting), and quality and reliability of technical infrastructure.
- 3 years of experience with hardware debug (silicon debug, platform debug, IO interface, or memory analysis).
- Experience debugging technical issues across the stack (hardware faults, low-level software, networking, virtualization, kernel drivers, firmware, or performance).
- Experience with Linux/Unix systems and debugging issues across the hardware/software boundary on enterprise-grade server infrastructure.
Preferred qualifications:
- Experience working with distributed systems, and familiarity with common solutions, design patterns, or best practices.
- Experience working directly with AI/ML computing hardware, including GPUs or other accelerators.
- Familiarity with containerization and orchestration technologies like Kubernetes or Slurm in an on-prem or cloud environment.
- Experience with systems automation, and with systems design and debug.
- Experience with ML frameworks (e.g., TensorFlow, PyTorch), and understanding of the AI/ML training and inference lifecycle.
- Advanced understanding of memory and high-speed input/output (IO) technologies.
About the job
Our AI Infrastructure Engineering Support team is dedicated to ensuring our customers get the most out of their Google Cloud hardware investment. As a Platform Application Engineer (Hardware Engineer), you will be focused on solving customer observations by, driving deep hardware analysis, debug, and issue resolution through to root cause. You will dive deep into complex technical challenges, troubleshoot critical issues across the platform, and provide resolutions in both short-term and long-term platform solutions. In this role, you will represent the customer solution, collaborating tightly with engineering and product teams to drive continuous improvement in our products and services.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $159000 - $230000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Manage customer’s problems through effective diagnosis, resolution, or implementation of new investigation tools to increase productivity on AI/ML infrastructure.
- Work closely with multiple Product, Quality, and Engineering teams to improve the product, and interact with our Site Reliability Engineering (SRE) teams to understand behaviours.
- Debug platform hardware and silicon-related issues to drive root-cause resolution and develop permanent improvements.
- Drive understanding of AI/ML workloads and underlying hardware architectures by troubleshooting, reproducing, determining the cause for customer reported issues, and building tools for faster diagnosis.
- Act as a consultant and subject matter expert for internal stakeholders in Engineering and Quality organizations to resolve complex deployment and operational obstacles in AI infrastructure environments.
- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Austin, TX, USA; Kirkland, WA, USA.
Minimum qualifications:
- Bachelor's degree in Computer Science, Management Information Systems, or other technical field, or equivalent practical experience.
- 4 years of debug or validation experience with CPU, dGPU, or TPU.
- 4 years of experience with technical infrastructure (deployment, maintenance, and troubleshooting), and quality and reliability of technical infrastructure.
- 3 years of experience with hardware debug (silicon debug, platform debug, IO interface, or memory analysis).
- Experience debugging technical issues across the stack (hardware faults, low-level software, networking, virtualization, kernel drivers, firmware, or performance).
- Experience with Linux/Unix systems and debugging issues across the hardware/software boundary on enterprise-grade server infrastructure.
Preferred qualifications:
- Experience working with distributed systems, and familiarity with common solutions, design patterns, or best practices.
- Experience working directly with AI/ML computing hardware, including GPUs or other accelerators.
- Familiarity with containerization and orchestration technologies like Kubernetes or Slurm in an on-prem or cloud environment.
- Experience with systems automation, and with systems design and debug.
- Experience with ML frameworks (e.g., TensorFlow, PyTorch), and understanding of the AI/ML training and inference lifecycle.
- Advanced understanding of memory and high-speed input/output (IO) technologies.
About the job
Our AI Infrastructure Engineering Support team is dedicated to ensuring our customers get the most out of their Google Cloud hardware investment. As a Platform Application Engineer (Hardware Engineer), you will be focused on solving customer observations by, driving deep hardware analysis, debug, and issue resolution through to root cause. You will dive deep into complex technical challenges, troubleshoot critical issues across the platform, and provide resolutions in both short-term and long-term platform solutions. In this role, you will represent the customer solution, collaborating tightly with engineering and product teams to drive continuous improvement in our products and services.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $159000 - $230000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Manage customer’s problems through effective diagnosis, resolution, or implementation of new investigation tools to increase productivity on AI/ML infrastructure.
- Work closely with multiple Product, Quality, and Engineering teams to improve the product, and interact with our Site Reliability Engineering (SRE) teams to understand behaviours.
- Debug platform hardware and silicon-related issues to drive root-cause resolution and develop permanent improvements.
- Drive understanding of AI/ML workloads and underlying hardware architectures by troubleshooting, reproducing, determining the cause for customer reported issues, and building tools for faster diagnosis.
- Act as a consultant and subject matter expert for internal stakeholders in Engineering and Quality organizations to resolve complex deployment and operational obstacles in AI infrastructure environments.
See All 32 Senior Cloud Platform Engineer Jobs in Austin
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Find JobsSenior Cloud Platform Engineer Job Market in Austin
Who's Hiring
- Google13
- PEAK63
- Emerson3
- TTEC Digital3
- Amazon Web Services3
Senior Cloud Platform Engineer Jobs in Austin: Frequently Asked Questions
How do I get a senior cloud platform engineer job in Austin?
Focus your search on Austin's concentrated tech corridors: the Domain hosts major cloud and semiconductor employers, while downtown and East Austin hold fintech and SaaS companies actively hiring at the senior level. Candidates with deep Kubernetes, Terraform, or multi-cloud architecture experience stand out here. Contributing to Austin's active open-source and DevOps meetup scene also builds visibility with local engineering teams before a job opens.
Which companies hire senior cloud platform engineers in Austin?
Companies currently hiring senior cloud platform engineers in Austin include Google, PEAK6, and Emerson, per current listings on Migrate Mate as of September 2026. Austin's market includes a mix of global tech giants with large regional campuses, high-growth SaaS startups, and financial services firms that have relocated headquarters or major engineering hubs to the city.
Are there remote senior cloud platform engineer jobs in Austin?
Yes, though senior cloud platform engineering skews toward hybrid arrangements given the hands-on infrastructure and cross-team coordination the role requires. About 100% of senior cloud platform engineer openings tied to Austin are remote or hybrid as of September 2026, reflecting strong employer flexibility at the senior level. Architecture design, policy work, and cloud cost optimization are the functions Austin teams most commonly allow to run fully remote.
How can I get a senior cloud platform engineer job in Austin with little or no experience?
The most realistic entry path in Austin is landing a cloud operations or site reliability engineer role at one of the city's mid-size SaaS companies or managed service providers, then building toward a platform engineering scope. Austin's UT and ACC graduate pipeline means local employers are accustomed to hiring candidates who pair a strong cloud certification with a project portfolio. Internal transfers from DevOps or systems administration roles at Austin's larger tech campuses are also a common door.
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