Cloud Platform Engineer Jobs in Texas
Cloud Platform Engineer jobs in Texas are in strong demand, concentrated in enterprise technology, energy, financial services, and healthcare sectors, with openings at every level from junior engineers to principal architects. Austin, Dallas, and Houston lead hiring volume, anchored by large employers like Dell Technologies, AT&T, and ExxonMobil, all of which maintain significant cloud infrastructure operations in the state. The most sought-after specialties include Kubernetes orchestration, multi-cloud architecture across AWS and Azure, and platform DevSecOps. Find a role that fits below and apply directly.
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- 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 Cloud Platform Engineer Jobs in Texas
Find roles in Texas that match your experience and apply in just a few clicks.
Find Cloud Platform Engineer JobsCloud Platform Engineer Jobs by City in Texas
Where Texas roles are concentrated, by current openings.
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 cloud platform engineer jobs across Texas.
- Bachelor's degree in computer science, information systems, or a related engineering field
- Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud
- Proficiency with infrastructure-as-code tools including Terraform, Pulumi, or AWS CloudFormation
- Experience designing and operating Kubernetes clusters and containerized workloads at scale
- Strong knowledge of CI/CD pipeline design, GitOps workflows, and DevSecOps practices
- Relevant cloud certifications such as AWS Solutions Architect, CKA, or Azure DevOps Engineer
Cloud Platform Engineer Jobs in Texas: Frequently Asked Questions
How do you become a cloud platform engineer in Texas?
Cloud platform engineering in Texas has no state-issued license or registration requirement, so the path runs through education and credentials. Most Texas employers expect a bachelor's degree in computer science, information technology, or systems engineering, followed by hands-on cloud experience. Industry certifications from AWS, Microsoft, or the Cloud Native Computing Foundation carry real weight in Texas hiring pipelines and often substitute for advanced degrees when paired with a strong project portfolio.
How much do cloud platform engineers make in Texas?
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 cloud platform engineers in Texas?
Employers hiring 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 Fortune 500 headquarters and large energy and financial services firms means demand comes from both established enterprise IT departments and fast-growing technology divisions within those organizations.
Which Texas cities have the most cloud platform engineer jobs?
Austin, Plano, and Irving have the most cloud platform engineer openings in Texas. Austin's dense technology company ecosystem and corporate relocations drive volume there, while Dallas benefits from major telecommunications and financial services headquarters, and Houston's energy sector giants have invested heavily in cloud modernization programs that generate consistent platform engineering demand.
Are there remote cloud platform engineer jobs in Texas?
Yes, and more than most fields. Cloud platform engineering is inherently infrastructure-focused work that translates well to distributed teams, so remote arrangements are common. About 92% of cloud platform engineer openings tied to Texas are remote or hybrid as of September 2026, reflecting how normalized distributed work has become in this discipline. Platform automation, monitoring, and architecture design tasks are the functions most frequently offered as fully remote.
How can I get hired as a cloud platform engineer in Texas with little or no experience?
The most realistic entry path is a site reliability engineer associate or junior DevOps role at a large Texas employer, then moving laterally into platform work. Dell Technologies, AT&T, and major Houston-area energy firms run structured early-career technology programs that accept candidates without industry experience if they hold a relevant degree or an AWS or Azure foundational certification. Building a public portfolio on GitHub demonstrating Terraform configurations and Kubernetes deployments gives candidates from adjacent roles like systems administrator or software developer a concrete edge in Texas interviews.
Where can I find and apply to cloud platform engineer jobs in Texas?
You can find and apply to cloud platform engineer jobs in Texas on Migrate Mate, which lists current Texas openings across Austin, Dallas, Houston, and other markets in the state. Search the listings for roles that match your experience level and specialization, then apply directly to the ones that fit.
See All 32 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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