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Ai Infrastructure Jobs in Florida (NOW HIRING)

Anson McCade

AI Researcher / AI Engineer

Miami, FL · On-site

$250K/yr

Distributed systems and AI infrastructure You'll tackle challenging mathematical and engineering problems while building scalable, production-ready AI solutions in a highly collaborative and research ...

Deloitte

AI Datacenter Associate VP

Tampa, FL · Hybrid

AI Datacenter & Infrastructure Associate VP Join our AI & Engineering team and help transform technology platforms, drive innovation, and make a significant impact on our clients' success. You'll ...

Deloitte

AI Datacenter Associate VP

Miami, FL · Hybrid

AI Datacenter & Infrastructure Associate VP Join our AI & Engineering team and help transform technology platforms, drive innovation, and make a significant impact on our clients' success. You'll ...

Rumble

Senior Infrastructure Engineer - DNS

Miami, FL · On-site

$132K - $158K/yr

RUM Group Inc. is an AI infrastructure and video company. Its Quake AI business delivers AI compute as a service, operating AI data centers including GPU and CPU compute, storage, and networking at ...

Rumble

Senior Infrastructure Engineer - DNS

Sarasota, FL · On-site

$132K - $158K/yr

RUM Group Inc. is an AI infrastructure and video company. Its Quake AI business delivers AI compute as a service, operating AI data centers including GPU and CPU compute, storage, and networking at ...

Edgeuno

Managing Director, EdgeUno Compute

Miami, FL · On-site

$150 - $200/hr

The ideal candidate should be a highly execution-oriented infrastructure leader with deep experience operating cloud, compute, data center, or AI infrastructure businesses at scale. This person ...

Rumble

Project Manager - Cloud/Infrastructure

Bradenton, FL · On-site

$125K - $150K/yr

RUM Group Inc. is an AI infrastructure and video company. Its Quake AI business delivers AI compute as a service, operating AI data centers including GPU and CPU compute, storage, and networking at ...

Rumble

Project Manager - Cloud/Infrastructure

Miami, FL

$125K - $150K/yr

RUM Group Inc. is an AI infrastructure and video company. Its Quake AI business delivers AI compute as a service, operating AI data centers including GPU and CPU compute, storage, and networking at ...

Rumble

Project Manager - Cloud/Infrastructure

Sarasota, FL · On-site

$125K - $150K/yr

RUM Group Inc. is an AI infrastructure and video company. Its Quake AI business delivers AI compute as a service, operating AI data centers including GPU and CPU compute, storage, and networking at ...

Rumble

Senior Infrastructure Engineer - CDN

Sarasota, FL · On-site

$132K - $158K/yr

RUM Group Inc. is an AI infrastructure and video company. Its Quake AI business delivers AI compute as a service, operating AI data centers including GPU and CPU compute, storage, and networking at ...

Rumble

Senior Infrastructure Engineer - CDN

Miami, FL

$132K - $158K/yr

RUM Group Inc. is an AI infrastructure and video company. Its Quake AI business delivers AI compute as a service, operating AI data centers including GPU and CPU compute, storage, and networking at ...

Rumble

Senior Infrastructure Engineer - DDOS

Sarasota, FL · Remote

$132K - $158K/yr

RUM Group Inc. is an AI infrastructure and video company. Its Quake AI business delivers AI compute as a service, operating AI data centers including GPU and CPU compute, storage, and networking at ...

Rumble

Senior Infrastructure Engineer - DDOS

Miami, FL · Remote

$132K - $158K/yr

RUM Group Inc. is an AI infrastructure and video company. Its Quake AI business delivers AI compute as a service, operating AI data centers including GPU and CPU compute, storage, and networking at ...

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Ai Infrastructure information

See Florida salary details

$21

$44

$65

How much do ai infrastructure jobs pay per hour?

As of Aug 26, 2026, the average hourly pay for ai infrastructure in Florida is $44.23, according to ZipRecruiter salary data. Most workers in this role earn between $35.91 and $51.54 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 Florida?

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

What job categories do people searching Ai Infrastructure jobs in Florida look for?

The top searched job categories for Ai Infrastructure jobs in Florida are:

What cities in Florida are hiring for Ai Infrastructure jobs?

Cities in Florida with the most Ai Infrastructure job openings:

Ai Infrastructure jobs near you
Infographic showing various Ai Infrastructure job openings in Florida as of August 2026, with employment types broken down into 78% Full Time, 20% Part Time, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution, with an average salary of $91,994 per year, or $44.2 per hour.

AI Infrastructure & Platform Engineer

International Materials Inc

Delray Beach, FL • On-site

$100K - $132K/yr

Full-time

Posted 6 days ago

Job description

Description:

IMI is seeking an AI Infrastructure & Platform Engineer to help build and expand our internal AI capabilities.

This is a hands-on opportunity to work across AI, software development, cloud infrastructure, and systems integration as we develop a scalable and secure foundation for AI across the organization.


Working alongside internal teams and external technology partners, this individual will help design and build our internal AI platform, develop AI-powered workflows and integrations, and bring more AI capabilities in-house over time. The role will also help evaluate when to build solutions internally, when to leverage third-party technologies, and how to securely and reliably bring those solutions into production.


The ideal candidate combines a strong software and cloud infrastructure foundation with hands-on experience with large language models (LLMs), generative AI, and modern AI application architectures. This person will also serve as an internal advocate for AI adoption, helping technical and non-technical users understand and effectively utilize new AI-powered tools.

Requirements:
  • 5+ years of professional experience in software development, cloud infrastructure, platform engineering, MLOps, DevOps, or a related technical field.
  • Strong software development fundamentals with experience building, deploying, and supporting production applications or services.
  • Hands-on experience with at least one major cloud platform such as AWS, Azure, or GCP.
  • Experience with modern software deployment practices, including CI/CD and development, staging, and production environments.
  • Experience developing and maintaining APIs and integrations between applications, cloud platforms, data sources, and third-party services.
  • Hands-on familiarity with modern AI technologies, LLMs, generative AI, and production AI/ML systems.
  • Understanding of application, infrastructure, and data security best practices.
  • Strong written and verbal English communication skills with the ability to explain technical concepts to both technical and non-technical audiences.
  • Resourceful, collaborative, and comfortable working independently in an evolving technical environment.
  • Ability to champion new technologies and work effectively across the organization to support AI adoption.

Preferred Qualifications

  • Experience with AI agents, RAG, vector databases, AI orchestration frameworks, or LLM-powered workflows.
  • Experience with cloud-native and infrastructure technologies such as Docker, Kubernetes, Terraform, or similar tools.
  • Familiarity with Model Context Protocol (MCP) or similar AI integration standards.
  • Experience with technologies such as Anthropic Claude, OpenAI, Google Gemini, Hugging Face, LangChain, LangGraph, or comparable AI platforms and frameworks.
  • Experience customizing, fine-tuning, or deploying private or domain-specific language models.
  • Experience working with sensitive financial, trading, or other regulated data.
  • Familiarity with SOC 2 or similar security, compliance, and data governance frameworks.
  • Full-stack development experience is a plus.
  • Relevant cloud or AI certifications are a plus.
  • 5+ years of professional experience in software development, cloud infrastructure, platform engineering, MLOps, DevOps, or a related technical field.
  • Strong software development fundamentals with experience building, deploying, and supporting production applications or services.
  • Hands-on experience with at least one major cloud platform such as AWS, Azure, or GCP.
  • Experience with modern software deployment practices, including CI/CD and development, staging, and production environments.
  • Experience developing and maintaining APIs and integrations between applications, cloud platforms, data sources, and third-party services.
  • Hands-on familiarity with modern AI technologies, LLMs, generative AI, and production AI/ML systems.
  • Understanding of application, infrastructure, and data security best practices.
  • Strong written and verbal English communication skills with the ability to explain technical concepts to both technical and non-technical audiences.
  • Resourceful, collaborative, and comfortable working independently in an evolving technical environment.
  • Ability to champion new technologies and work effectively across the organization to support AI adoption.

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