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Ai Infrastructure Jobs in Spring, TX (NOW HIRING)

Developer & Infrastructure Expert Role Type: Contractor Location: Remote Job Overview We are ... You will test AI-generated commands, configurations, and workflows and provide practical feedback ...

This is a foundational role: there is no pre-existing AI infrastructure or precedent at FSCU, and the work performed in this position will establish the technical foundation upon which AI at FSCU is ...

This is a foundational role: there is no pre-existing AI infrastructure or precedent at FSCU, and the work performed in this position will establish the technical foundation upon which AI at FSCU is ...

This is a foundational role: there is no pre-existing AI infrastructure or precedent at FSCU, and the work performed in this position will establish the technical foundation upon which AI at FSCU is ...

Remote Job Summary We are seeking an experienced AI/ML Engineer to build and deploy secure, scalable AI solutions for mission-critical initiatives while contributing to proprietary AI infrastructure.

Senior AI Engineer - AAET

Houston, TX · On-site

$99K - $137K/yr

Collaborate with platform, security, and infrastructure teams to ensure AI systems meet enterprise requirements for identity, access, data governance, and operational support * Evaluate the ...

Showing results 21-40

Ai Infrastructure information

See Spring, TX salary details

$25

$52

$77

How much do ai infrastructure jobs pay per hour?

As of Sep 2, 2026, the average hourly pay for ai infrastructure in Spring, TX is $52.67, according to ZipRecruiter salary data. Most workers in this role earn between $42.79 and $61.39 per hour, depending on experience, location, and employer.

What is AI infrastructure?

AI infrastructure refers to the combination of hardware, software, and cloud-based solutions that support the development, deployment, and scaling of artificial intelligence applications. It includes components such as GPUs, CPUs, storage systems, networking, data management tools, and machine learning frameworks. The goal of AI infrastructure is to provide the computational power and resources needed to train, test, and run AI models efficiently, whether on-premises or in the cloud. Organizations invest in robust AI infrastructure to accelerate innovation, manage large datasets, and ensure the reliability of their AI systems.

What are the key skills and qualifications needed to thrive in AI infrastructure?

To thrive in AI Infrastructure, you need expertise in software engineering, distributed systems, cloud platforms, and a solid understanding of machine learning workflows, often supported by degrees in computer science or related fields. Familiarity with tools like Kubernetes, Docker, Terraform, and cloud services (AWS, GCP, Azure), as well as experience with CI/CD pipelines and monitoring systems, is essential. Strong problem-solving abilities, effective communication, and adaptability help professionals excel in cross-functional teams and rapidly evolving environments. These skills and qualities are crucial for building scalable, reliable systems that power AI applications and support organizational innovation.

What are common challenges faced by professionals working in AI infrastructure roles, and how can they be addressed?

Professionals in AI Infrastructure roles often encounter challenges related to scalability, system reliability, and integration with existing IT environments. Managing rapidly growing datasets and ensuring seamless deployment of machine learning models can be complex, requiring robust automation and monitoring tools. Collaboration with data scientists, software engineers, and DevOps teams is critical to ensure infrastructure meets the evolving needs of AI projects. Staying updated with the latest cloud technologies and best practices can help address these challenges and drive successful AI implementations.

What is the difference between Ai Infrastructure vs Data Engineer?

AspectAi InfrastructureData Engineer
Required CredentialsBachelor's in CS, Engineering, or related; knowledge of cloud platforms and AI toolsBachelor's in CS, Data Science, or related; programming and database skills
Work EnvironmentCloud environments, AI model deployment, infrastructure setupData pipelines, database management, data processing
Employer & Industry UsageTech companies, AI startups, cloud providersTech firms, finance, healthcare, e-commerce

Ai Infrastructure professionals focus on building and maintaining the hardware and software systems that support AI models, while Data Engineers develop and manage data pipelines and databases. Both roles require technical skills and often collaborate but serve different core functions within AI and data ecosystems.

What are AI infrastructure jobs?

AI infrastructure jobs involve designing, building, and maintaining the hardware, software, and network systems necessary to support artificial intelligence applications. These roles often require knowledge of cloud computing, data centers, machine learning frameworks, and system optimization to ensure reliable and efficient AI model deployment and operation.

What are popular job titles related to Ai Infrastructure jobs in Spring, TX?

For Ai Infrastructure jobs in Spring, TX, the most frequently searched job titles are:

What job categories do people searching Ai Infrastructure jobs in Spring, TX look for?

The top searched job categories for Ai Infrastructure jobs in Spring, TX are:

What cities near Spring, TX are hiring for Ai Infrastructure jobs?

Cities near Spring, TX with the most Ai Infrastructure job openings:

Infographic showing various Ai Infrastructure job openings in Spring, TX as of August 2026, with employment types broken down into 81% Full Time, 17% Part Time, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution, with an average salary of $109,548 per year, or $52.7 per hour.

WW Networks for AI Channel Leader

Hewlett Packard Enterprise Development LP

Spring, TX • On-site

Full-time

Posted 22 days ago


Hewlett Packard Enterprise rating

8.4

Company rating: 8.4 out of 10

Based on 26 frontline employees who took The Breakroom Quiz

36th of 159 rated electronics manufacturers


Job description

WW Networks for AI Channel Leader
This role has been designed as 'Hybrid' with a requirement that you will work on average 2 days per week from an HPE office.
Who We Are:
Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today's complex world. Our culture thrives on finding new and better ways to accelerate what's next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.
Job Description:
Role Summary
The Leader, WW Networks for AI Channel Leader is responsible for defining and executing the global channel strategy for AI-native networking, enabling partners to capitalize on the accelerating demand for AI workloads, distributed architectures, and self-driving networks.
This role spans all partner types (Geo, Distribution, and Strategic Partners) and is focused on positioning the channel to deliver AI-optimized networking infrastructure, automation, and security at scale.
This is a WW overlay leadership role that:
  • Provides strategic direction and governance across GEOs
  • Drives AI networking priorities, programs, and partner motions
  • Acts as the global voice for Networks for AI in the channel ecosystem
Key Responsibilities
Worldwide Channel Strategy & Governance (AI Networking)
  • Define the WW Networks for AI channel strategy, aligned to:
    • AI workload growth (training, inference, distributed data pipelines)
    • AI-native, self-driving networking operating models
    • Unified client-to-cloud infrastructure
  • Establish global standards for:
    • Partner specialization in AI networking architectures (fabric, edge, data centre)
    • AI-native operational capabilities (AIOps, automation, observability)
    • Experience-led success metrics (performance, automation, user experience)
  • Drive alignment across GEO channel leaders to ensure consistent execution of:
    • AI networking priorities (performance, scale, automation, security)
    • Transition from traditional networking to AI-native, self-driving models
Partner Ecosystem Leadership (AI-Ready Partners)
  • Serve as the global leader for partners building Networks for AI capabilities, including:
    • AI data centre networking (high-performance Ethernet fabrics)
    • Cloud-to-edge AI connectivity
    • AI-driven operations and automation
  • Shape partner investment strategies toward:
    • AI-optimized infrastructure and services
    • Development of AI-ready networking practices and IP
    • Integration of networking, security, and AI operations
  • Identify ecosystem gaps in:
    • AI networking capacity, skills, and coverage
    • Partner readiness to support large-scale AI deployments
    • Alignment with AI-driven TAM expansion
Voice to the Channel Market (AI Networking Leadership)
  • Represent HPE Networking at:
    • Global and regional partner events focused on AI and infrastructure transformation
    • Analyst briefings on AI-native networking and self-driving networks
    • Executive partner forums, PABs, and industry engagements
  • Position HPE as the leader in:
    • Self-driving networks purpose-built for AI
    • AI-native infrastructure (client-to-cloud, unified platform)
    • Integrated Zero Trust security for AI environments
Cross-Functional Leadership (AI GTM Alignment)
  • Partner with Sales, Engineering, and GTM teams to align:
    • Channel strategy with AI networking solutions and roadmaps
    • Partner enablement on AI workloads, fabrics, and automation
    • Incentives and programs to accelerate AI networking adoption
  • Ensure alignment across:
    • Compute, storage, and networking teams to deliver end-to-end AI infrastructure plays
    • Security integration (Zero Trust, SASE) within AI networking architectures
Incubation & Scale (AI Networking Curve)
  • Lead the incubation of Networks for AI in the channel, recognising that:
    • Traditional coverage and ratios are insufficient for AI-driven complexity
    • New partner skills (automation, AI ops, data centre fabrics) are required
  • Drive:
    • Early partner specialisation in AI networking use cases
    • Development of repeatable AI deployment motions (training clusters, inference edge, hybrid AI)
    • Transition from incubation to scaled, repeatable global execution
Success Measures
  • Clear and adopted WW Networks for AI channel strategy
  • Strong partner capability in:
    • AI networking infrastructure
    • AI-driven operations (automation, AIOps, self-driving)
  • Increased partner-led growth in:
    • AI networking deals
    • Data centre, edge, and hybrid AI deployments
  • Improved market perception of HPE as:
    • Leader in AI-native, self-driving networking
    • Provider of secure, high-performance AI infrastructure at scale
Ideal Experience & Profile
  • 5+ years of experience in networking, AI infrastructure, or data centre architectures
  • Bachelors degree or equivalent work experience
  • Proven leadership in global channel strategy and ecosystem development
  • Understanding of:
    • AI workloads and infrastructure requirements
    • High-performance networking (fabric, routing, low latency architectures)
    • Automation, AIOps, and AI-native operations
  • Experience operating in Regional or WW roles influencing GEO execution without direct control
  • Strong executive presence with:
    • Hyperscalers, GSIs, or AI-focused partners
    • Analysts and industry forums
  • Ability to lead transformation toward:
    • AI-native infrastructure
    • Self-driving networking models
    • Integrated security and Zero Trust architectures

What We Can Offer You:
Health & Wellbeing
We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.
Personal & Professional Development
We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have - whether you want to become a knowledge expert in your field or apply your skills to another division.
Unconditional Inclusion
We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.
Let's Stay Connected:
Follow @HPECareers on Instagram to see the latest on people, culture and tech at HPE.
Job:
Sales
Job Level:
Manager_2
"The expected salary/wage range for this position is provided below. Actual offer may vary from this range based upon geographic location, work experience, education/training, and/or skill level.
- United States of America: Annual Salary USD 216,000 - 507,000 in Texas
This range reflects the minimum to maximum combined base and target-level sales compensation that would be paid if the hire performs at 100% of their sales plan. Of that on-target pay amount, the mix of base salary and target-level sales compensation is 60%/40%."
Information about employee benefits offered in the US can be found at https://myhperewards.com/main/new-hire-enrollment.html
HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity.
Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.
HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.
Recruitment Fraud Alert
We have become aware of an increase in fraudulent recruitment activities in which individuals impersonate our company or authorized recruitment agencies to offer fake employment opportunities. These scams may occur through false websites, emails, social media, or chat-based applications and often aim to obtain personal information or money. Please note that Hewlett Packard Enterprise (HPE), its direct and indirect subsidiaries and affiliated companies, and its authorized recruitment agencies/vendors will never charge a candidate a registration fee, hiring fee, or any other fee in connection with its recruitment and hiring process. We also never request personal information such as back account details, Social Security numbers, or national IDs via social media or chat applications.
All legitimate job opportunities will come through official company channels, and candidates are responsible for verifying the credentials of any third party claiming to represent the company. Any reliance on fraudulent communication is at the individual's own risk, and HPE disclaims legal liability for any resulting damages. If you suspect recruitment fraud, do not share personal information or make any payments and report the incident to your local authorities immediately.

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