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From Home Ai Developer Jobs in Arizona (NOW HIRING)

Java Springboot AI Developer

Phoenix, AZ ยท On-site

$50.75 - $65.50/hr

... phases from requirement gathering to implementation. โ€ข A knack for translating complex ... We do it by enabling the enterprise with an AI-powered core that helps prioritize the execution of ...

Java Springboot AI Developer

Phoenix, AZ ยท On-site

$90 - $120/hr

We specialize in leveraging advanced technologies such as AI, cloud, and dataโ€‘led innovation to ... The ability to handle end to end SDLC phases from requirement gathering to implementation. * A ...

AI Engineer

Phoenix, AZ ยท On-site

$125K - $175K/yr

As AI Engineer, you will ... Build MVPs from scratch: take new AI products from zero to real users - both consumer-facing and ...

AI Engineer

Phoenix, AZ ยท On-site

$125K - $175K/yr

As AI Engineer, you will ... Build MVPs from scratch: take new AI products from zero to real users -- both consumer-facing and ...

AI Engineer

Phoenix, AZ

$125K - $175K/yr

As AI Engineer, you will ... Build MVPs from scratch: take new AI products from zero to real users - both consumer-facing and ...

... from the following list: AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI Practitioner (AIF-C01), AWS Certified Generative AI Developer (Professional ...

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From Home Ai Developer information

What does a from home AI developer do?

A From Home AI Developer designs, develops, and implements artificial intelligence solutions while working remotely. Their tasks often include building machine learning models, creating algorithms, analyzing data, and integrating AI functionalities into software applications. They typically collaborate with other team members online, using various communication and development tools. This role requires strong programming skills, expertise in AI frameworks, and the ability to work independently from a remote location.

What are the key skills and qualifications needed to thrive as a from home AI developer, and why are they important?

To thrive as a From Home AI Developer, you need a strong background in computer science, programming (Python, Java, or C++), and machine learning concepts, often supported by a relevant degree or certifications. Familiarity with AI frameworks (TensorFlow, PyTorch), cloud platforms (AWS, Azure), and version control systems (Git) is typically required. Critical thinking, self-motivation, and effective remote communication are essential soft skills for success in a distributed team environment. These skills enable efficient development, problem-solving, and collaboration, ensuring the delivery of robust AI solutions from a remote setting.

How do remote AI developers typically collaborate with team members when working from home?

Remote AI Developers often collaborate using a variety of digital tools, such as version control systems (like Git), video conferencing platforms, and project management software. Regular virtual meetings and code reviews are common to ensure alignment on project goals and maintain code quality. Effective communication skills and proactive updates are essential, as team members may be spread across different time zones. Most teams also use instant messaging apps for quick problem-solving and brainstorming, fostering a collaborative environment despite the distance.

What is the difference between From Home Ai Developer vs From Home Data Scientist?

AspectFrom Home Ai DeveloperFrom Home Data Scientist
Required CredentialsBachelor's in CS, AI, or related field; knowledge of machine learning frameworksBachelor's or higher in Statistics, CS, or related; strong analytical skills
Work EnvironmentRemote, tech companies, AI-focused projectsRemote, data-driven organizations, research or analytics teams
Employer & Industry UsageTech firms, startups, AI product companiesFinance, healthcare, tech, research institutions
Common Search & Comparison IntentUnderstanding roles in AI development from homeComparing data science roles with AI development

From Home Ai Developer and From Home Data Scientist share similarities in remote work settings and required technical skills. However, AI Developers focus on creating AI models and applications, while Data Scientists analyze data to extract insights. Both roles are vital in tech industries but serve different functions within AI and data analysis domains.

What are the most commonly searched types of Ai Developer jobs in Arizona?

The most popular types of Ai Developer jobs in Arizona are:

What cities in Arizona are hiring for From Home Ai Developer jobs?

Cities in Arizona with the most From Home Ai Developer job openings:

Principal Platform Engineer, AI - Automation

Jobtailor

Phoenix, AZ โ€ข On-site

$170 - $210/hr

Other

Posted 8 days ago


Job description

  • Write high-quality, maintainable code that accelerates platform automation and reduces tech debt across Global Host Platform systems.
  • Build the internal tools that keep our systems scalable and resilient at global scale โ€” engineered to hold up under the peak load of high-demand onsales.
  • Use scripting (Python, Bash) and infrastructure-as-code (Terraform, Ansible) to simplify and standardize operational workflows.
  • Lead technical deep-dives to spot automation opportunities and tackle long-standing inefficiencies.
  • Drive adoption of AI developer tools โ€” e.g. Claude Code, GitHub Copilot, Cursor, Amazon Q, and local models via Ollama โ€” across the team.
  • Design and champion agentic AI workflows that plan, reason, and act โ€” building frameworks for autonomous task execution and tool chaining, including via the Model Context Protocol (MCP).
  • Define and evolve our internal patterns for LLM-backed development, spec-driven workflows, and AI-augmented refactoring โ€” with attention to code quality, security, and human review.
  • Define and evangelize internal standards for platform automation, SRE practice, and code quality.
  • Mentor engineers and spread knowledge across the team, especially on getting real leverage from modern AI tooling.
  • Partner with reliability and platform engineers to deliver automation that sticks โ€” measurable impact over buzzwords.
  • Lead in-person team trainings, gatherings, and hackathons on-site monthly, and travel quarterly.

Requirements

  • 8+ years of hands-on software engineering experience; systems or backend engineering preferred.
  • Hands-on experience with AI developer tools (Claude Code, GitHub Copilot, Cursor, etc.), LLM-backed scripting, and agentic AI systems capable of planning, tool use, and autonomous task execution in engineering workflows.
  • Agentic AI in both our developer processes and our production services is a must โ€” you build with it day-to-day and you run it where reliability actually counts.
  • Strong command of multiple scripting languages and infrastructure-as-code tooling.
  • Experience with automated VM deployments (VMware) and automated configuration management (Ansible).
  • Containerizing software and tools (Docker, Podman) and deploying them in orchestrated environments (Kubernetes).
  • Experience in SRE, DevOps, or platform engineering โ€” or the curiosity and track record to ramp up fast.
  • A genuine drive to reduce tech debt, enable teammates, and automate the annoying stuff.
  • Ability to lead a team in blending software engineering best practices with fast-moving AI capabilities โ€” and to keep that blend current as both continue to evolve.
  • A habit of keeping pace with a market that moves weekly, not yearly โ€” and the instinct to lead and teach others so the whole team stays current, not just you.
  • Excellent communication and collaboration skills; you enjoy being a multiplier.
  • Nice to have: Background in high-scale production systems (AWS, observability platforms, etc.).
  • Nice to have: Experience building or operating MCP servers, or integrating AI agents with internal tooling.
  • Nice to have: Experience introducing new development practices or tooling into an existing engineering org.
  • Nice to have: Prior involvement in incident management, disaster recovery, or reliability strategy.

Core Competencies

Demonstrates expertise in software engineering with a focus on automation, AI developer tools, and infrastructure-as-code practices. Proven ability to mentor teams, drive adoption of modern technologies, and enhance operational workflows for scalable and resilient systems.

Highest-signal resume keywords

  • Python Scripting
  • Infrastructure-As-Code (Terraform, Ansible)
  • AI Developer Tools (Claude Code, GitHub Copilot, Cursor)
  • Containerization (Docker, Podman)
  • Site Reliability Engineering (SRE)

ATS Optimization Keywords

Hard Skills

  • Software Engineering
  • Backend Engineering
  • Automated VM Deployments (VMware)
  • Automated Configuration Management (Ansible)
  • LLM-Backed Scripting
  • Agentic AI Systems
  • Code Quality Standards
  • Tech Debt Reduction
  • AI-Augmented Refactoring
  • Orchestrated Environments (Kubernetes)

Soft Skills

  • Excellent Communication
  • Collaboration
  • Mentoring
  • Leadership
  • Team Building

Industry Keywords

  • Platform Automation
  • DevOps
  • High-Scale Production Systems
  • Incident Management
  • Disaster Recovery

Tools & Technologies

  • Terraform
  • Ansible
  • Docker
  • Podman
  • Kubernetes
  • AWS
  • Observability Platforms
  • MCP Servers
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