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Site Reliability Engineer Remote Jobs in Arizona

... site reliability role at a software company * Comfortable reading logs, navigating Linux ... Mon-Fri hybrid (Wed remote); expectation is 80% in-office (Phoenix HQ) How We Hire (fast ...

Project Site Manager

Phoenix, AZ · Remote

$80K - $110K/yr

Coordinate with engineering, logistics, and project management teams to ensure seamless execution ... Willingness to travel and work on remote or international project sites as required. (50 ...

$150K/yr

... improve reliability and reduce interference. * Plan and validate RF design requirements by ... Proven experience with large-scale RF design projects involving high AP counts and multi-site ...

Proving Ground Site Lead

Phoenix, AZ · On-site +1

$230K - $284K/yr

Waymo's Systems Engineering team works together to blend software and hardware systems in ... remote, the specific salary range for your preferred location, during the hiring process. Waymo ...

Software Engineer

Phoenix, AZ · Remote

$110K - $135K/yr

Develop and run unit and performance tests to ensure scalability and reliability. * Review and ... Other Employee Perks Job Type: * Full-Time * Remote Compensation: * $110k - $135k DOE Required ...

This full-time, fully remote position offers the opportunity to collaborate with a talented team of ... Ensure performance, reliability, and scalability across all systems and applications. Continuously ...

Perform on-site installation, training, preventive maintenance, repairs, and upgrades of complex ... Provide remote service and visual support as required to ensure optimal product performance

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Site Reliability Engineer Remote information

See Arizona salary details

$10

$59

$85

How much do site reliability engineer remote jobs pay per hour?

As of Jun 13, 2026, the average hourly pay for site reliability engineer remote in Arizona is $59.40, according to ZipRecruiter salary data. Most workers in this role earn between $51.06 and $67.88 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Site Reliability Engineer Remote position, and why are they important?

To thrive as a Site Reliability Engineer Remote, you need expertise in systems administration, cloud infrastructure, automation, coding (often in Python or Go), and a solid grasp of networking fundamentals, usually demonstrated with a degree in computer science or equivalent experience. Familiarity with tools such as Docker, Kubernetes, AWS/GCP/Azure, monitoring platforms like Prometheus, and certifications like AWS Certified SysOps Administrator are highly valued. Excellent problem-solving, communication, and collaboration skills are essential, especially when troubleshooting incidents and passing information across distributed teams. These abilities ensure reliable, scalable services and smooth coordination in a remote work environment.

What is a Site Reliability Engineer Remote job?

A Site Reliability Engineer (SRE) in a remote role is responsible for ensuring the reliability, performance, and scalability of software systems while working from a remote location. They bridge the gap between development and operations by implementing automation, monitoring, and incident response strategies. Remote SREs collaborate with distributed teams to improve infrastructure, troubleshoot issues, and optimize system performance. Strong communication skills, proficiency in cloud technologies, and expertise in software development are essential for success in this role.

What are some common challenges faced by Site Reliability Engineers working remotely, and how are they addressed?

Site Reliability Engineers working remotely may encounter challenges like coordinating across multiple time zones, maintaining clear communication during urgent incidents, and managing complex systems without direct on-site access. These are often addressed by leveraging collaborative tools (like Slack, Zoom, and incident management platforms), implementing well-documented processes, and participating in regular team syncs or on-call rotations. Remote SREs also benefit from automation and observability practices that provide in-depth systems insights without needing physical presence. Many organizations support their success through robust onboarding, continuous training, and establishing clear lines of communication for rapid response scenarios. This blend of technical and teamwork strategies helps remote SREs maintain service reliability and stay connected with their colleagues.

What are the most commonly searched types of Site Reliability Engineer jobs in Arizona? The most popular types of Site Reliability Engineer jobs in Arizona are:
What job categories do people searching Site Reliability Engineer Remote jobs in Arizona look for? The top searched job categories for Site Reliability Engineer Remote jobs in Arizona are:
What cities in Arizona are hiring for Site Reliability Engineer Remote jobs? Cities in Arizona with the most Site Reliability Engineer Remote job openings:
Infographic showing various Site Reliability Engineer Remote job openings in Arizona as of June 2026, with employment types broken down into 73% Full Time, and 27% Contract. Highlights an 100% Remote job distribution, with an average salary of $123,553 per year, or $59.4 per hour.
Generative AI Automation Engineer - Remote Job

Generative AI Automation Engineer - Remote Job

EnthuZiastic

Scottsdale, AZ • Remote

Other

Posted 21 days ago


Job description

About Us

Our mission is to bring people together and connect them into a community to nurture each other. We aim to share a conducive environment, a joyous space to grow and excel; a world brimming with selfless love and enough kindness. We strive to enrich each of our lives with kaleidoscopic memories we make here - vibrant, lively, of all hues and colors.

Job Description

This is a remote position.

We are seeking a highly skilled and innovative Generative AI Automation Engineer to join our team. The ideal candidate will be responsible for designing, developing, and implementing automation solutions powered by Generative AI models. This role requires a combination of expertise in machine learning, natural language processing, software engineering, and automation frameworks to drive efficiency and innovation in business processes.

Key Responsibilities:

Generative AI Model Implementation:

  • Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks.

  • Integrate pre-trained models or build custom models for specific use cases.

Automation Design and Development:

  • Design and implement AI-driven workflows and solutions to automate repetitive tasks and improve process efficiency.

  • Develop APIs, scripts, and tools for seamless integration of AI models into existing systems.

Data Management:

  • Collect, preprocess, and analyze large datasets for training and validating AI models.

  • Ensure data privacy and compliance with regulatory requirements during data handling.

System Integration:

  • Collaborate with software development and IT teams to integrate Generative AI solutions with enterprise systems.

  • Build and maintain pipelines for real-time AI inference and automation.

Monitoring and Optimization:

  • Continuously monitor AI automation solutions to ensure accuracy, efficiency, and reliability.

  • Optimize models and processes based on performance metrics and user feedback.

Research and Innovation:

  • Stay updated with the latest advancements in Generative AI and automation technologies.

  • Identify opportunities for implementing cutting-edge AI solutions to address business challenges.

Documentation and Collaboration:

  • Document technical designs, workflows, and implementation strategies.

  • Collaborate with cross-functional teams, including product managers, data scientists, and software engineers.

Requirements

Required Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

  • Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face.

  • Proficiency in designing and deploying machine learning models, particularly in Generative AI.

  • Experience with automation tools (e.g., RPA, workflow orchestration tools).

  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes).

  • Solid understanding of data structures, algorithms, and software design principles.

  • Strong analytical and problem-solving skills.

  • Excellent communication and teamwork abilities.

Preferred Qualifications:

  • Experience with NLP, image generation, or multimodal AI models.

  • Hands-on experience with APIs for AI services like OpenAI, Cohere, or Google AI.

  • Familiarity with prompt engineering and fine-tuning Generative AI models.

  • Knowledge of MLOps practices for deploying and maintaining AI solutions.

  • Previous experience in automation or workflow optimization projects.

Benefits

Why Join Us?

  • Work with cutting-edge Generative AI technologies.

  • Collaborate with a team of forward-thinking innovators.

  • Make a tangible impact on the future of automation and AI-driven processes.

If you are passionate about leveraging Generative AI to create innovative automation solutions, we invite you to apply and be a part of our dynamic and growing team.