Senior Cloud Platform Engineer Jobs in Texas
Senior Cloud Platform Engineer jobs in Texas are among the most active in the country, with strong demand concentrated in energy technology, financial services, aerospace, and enterprise SaaS companies operating at scale. Austin, Dallas, and Houston lead hiring volume, and established employers like Dell Technologies, AT&T, and Lockheed Martin maintain large engineering workforces across the state. The most sought-after specialties in Texas are Kubernetes orchestration, multi-cloud architecture on AWS and Azure, and platform reliability engineering. 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 Texas
Find roles in Texas that match your experience and apply in just a few clicks.
Find JobsSenior Cloud Platform Engineer Jobs by City in Texas
Where Texas roles are concentrated, by current openings.
Senior Cloud Platform Engineer Job Market in Texas
A snapshot from current Texas openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Technology & Software
What Texas Employers Look For
The qualifications that appear most often in senior cloud platform engineer jobs across Texas.
- Bachelor's degree in computer science, engineering, or a closely related technical field
- Five or more years of hands-on cloud platform engineering or infrastructure engineering experience
- Deep expertise with AWS, Azure, or Google Cloud Platform at enterprise scale
- Proficiency with Kubernetes, Terraform, and infrastructure-as-code tooling and practices
- Experience designing and maintaining CI/CD pipelines and developer platform toolchains
- Strong background in platform observability, SRE practices, and incident response processes
Senior Cloud Platform Engineer Jobs in Texas: Frequently Asked Questions
How do you become a senior cloud platform engineer in Texas?
Senior cloud platform engineers in Texas typically hold a bachelor's degree in computer science or a related field and build several years of hands-on infrastructure and cloud engineering experience before reaching the senior level. Texas does not require a state-issued license for this role. Employers here consistently value industry certifications such as AWS Solutions Architect, Microsoft Azure Administrator, or Certified Kubernetes Administrator, and a portfolio demonstrating enterprise-scale platform work accelerates hiring.
How much do senior cloud platform engineers make in Texas?
Senior cloud platform engineers in Texas earn a median of about $132,150 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $82,600 for the lowest 10% to over $183,680 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire senior cloud platform engineers in Texas?
Employers hiring senior cloud platform engineers in Texas right now include Google, Emerson, and NTT DATA, based on current listings on Migrate Mate as of September 2026. Texas's concentration of energy, defense, and financial services headquarters means many of these employers operate large-scale, hybrid cloud environments that require experienced platform engineers year-round.
Which Texas cities have the most senior cloud platform engineer jobs?
Austin, Plano, and Irving have the most senior cloud platform engineer openings in Texas. Austin's high density of enterprise SaaS and semiconductor companies drives the bulk of postings there, while Dallas's major financial services and telecom headquarters and Houston's energy and aerospace sector sustain consistent demand across all three metros.
Are there remote senior cloud platform engineer jobs in Texas?
Yes, and more than most fields. About 92% of senior cloud platform engineer openings tied to Texas are remote or hybrid as of September 2026, reflecting how thoroughly this work is performed through cloud consoles and code rather than on physical hardware. Infrastructure design, platform tooling development, and SRE responsibilities are the responsibilities most often performed fully remotely.
How can I get hired as a senior cloud platform engineer in Texas with little or no experience?
The most realistic entry path is landing a cloud infrastructure associate or DevOps engineer role and building hands-on platform experience from there. Large Texas technology employers and state university systems such as the University of Texas and Texas A&M run internship and new-grad rotational programs in infrastructure and cloud engineering. Earning an entry-level cloud certification on AWS or Azure and contributing to open-source Kubernetes or Terraform projects gives candidates a concrete portfolio edge when competing for first roles.
Where can I find and apply to senior cloud platform engineer jobs in Texas?
You can find and apply to senior cloud platform engineer jobs in Texas on Migrate Mate, which lists current Texas openings across industries and metro areas. Find roles that match your experience and specialization and apply directly to the ones that fit.
See All 32 Senior Cloud Platform Engineer Jobs in Texas
Find roles in Texas that match your experience and apply in just a few clicks.
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