DevOps Developer
OR · Remote
Remote - United States / Canada What You'll Do: CI/CD, Build & Release Automation * Design ... Use AI-assisted tools responsibly to improve DevOps productivity, troubleshooting, documentation ...
DevOps Developer
OR · Remote
Remote - United States / Canada What You'll Do: CI/CD, Build & Release Automation * Design ... Use AI-assisted tools responsibly to improve DevOps productivity, troubleshooting, documentation ...
DevOps Developer
OR · On-site +1
Remote - United States / Canada What You'll Do: CI/CD, Build & Release Automation * Design ... Use AI-assisted tools responsibly to improve DevOps productivity, troubleshooting, documentation ...
DevOps Developer
OR · On-site +1
Remote - United States / Canada What You'll Do: CI/CD, Build & Release Automation * Design ... Use AI-assisted tools responsibly to improve DevOps productivity, troubleshooting, documentation ...
Remote Ai Image information
See Remote, OR salary details
$10.33 - $14.87
5% of jobs
$14.87 - $19.41
5% of jobs
$19.41 - $23.95
0% of jobs
$26.87 is the 25th percentile. Wages below this are outliers.
$23.95 - $28.49
22% of jobs
The median wage is $31.65 / hr.
$28.49 - $33.03
24% of jobs
$33.03 - $37.57
17% of jobs
$37.76 is the 75th percentile. Wages above this are outliers.
$37.57 - $42.11
13% of jobs
$42.11 - $46.65
5% of jobs
$46.65 - $51.20
2% of jobs
$51.20 - $55.74
5% of jobs
$55.74 - $60.28
0% of jobs
$10
$33
$60
How much do remote ai image jobs pay per hour?
As of Jul 20, 2026, the average hourly pay for remote ai image in Remote, OR is $33.89, according to ZipRecruiter salary data. Most workers in this role earn between $27.36 and $38.17 per hour, depending on experience, location, and employer.
What is a Remote AI Image Specialist?
A Remote AI Image Specialist is a professional who works from a remote location to create, enhance, or analyze images using artificial intelligence technologies. They may use machine learning models to generate realistic images, edit photos, or interpret visual data for various applications such as marketing, design, healthcare, or research. This role typically involves working with AI tools like generative adversarial networks (GANs), image recognition software, and editing platforms. Remote AI Image Specialists often collaborate with teams online and can work for companies or as freelancers. Strong technical skills and an understanding of AI-driven image processing are essential for this position.
What is a $900000 AI job?
A $900,000 AI job typically refers to a high-paying position in artificial intelligence, such as senior machine learning engineer, AI research director, or executive roles. These jobs often require advanced skills in deep learning, data analysis, and experience with AI tools, and may involve leadership responsibilities or specialized expertise. Compensation at this level reflects significant experience, impact, and sometimes equity or bonuses.
Can I make money from AI images?
Remote AI image jobs often involve creating or editing images using AI tools, and individuals can earn money by selling their AI-generated artwork, offering freelance services, or working for companies that utilize AI for visual content. Success depends on skill, creativity, and understanding of AI platforms like Midjourney or DALL·E, as well as building a portfolio or client base.
What is the difference between Remote Ai Image vs Remote Graphic Designer?
| Aspect | Remote Ai Image | Remote Graphic Designer |
|---|---|---|
| Required Skills | AI tools, image generation, machine learning basics | Design software, creativity, visual communication |
| Work Environment | Remote, tech-focused, collaborative with AI teams | Remote or on-site, creative studios or agencies |
| Industry Usage | Tech companies, AI startups, digital content creation | Advertising, marketing, branding agencies |
| Certifications | AI, machine learning, digital art courses | Design degrees, Adobe certifications |
Remote Ai Image specialists focus on generating images using AI tools and machine learning, often working within tech or AI-driven companies. In contrast, Remote Graphic Designers create visual content using traditional design software for various industries. While both roles require creativity, the skills and tools differ significantly, making each suited to different career paths and employer needs.
What are some common challenges faced by remote AI image specialists and how can they be overcome?
Remote AI image specialists often encounter challenges such as collaborating effectively across different time zones, ensuring high-quality data labeling, and managing large datasets securely. To overcome these, it's important to establish clear communication channels with team members, use collaboration tools for version control and feedback, and follow best practices for data privacy and transfer. Regular virtual meetings and thorough documentation can also help maintain project alignment and workflow efficiency.
What are the key skills and qualifications needed to thrive as a Remote AI Image Specialist, and why are they important?
To thrive as a Remote AI Image Specialist, you need a solid background in computer vision, image processing, and machine learning, often supported by a degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow, OpenCV, and cloud-based image annotation platforms is typically required. Strong problem-solving skills, self-motivation, and clear remote communication are vital soft skills for collaborating across distributed teams. These skills enable effective development, deployment, and refinement of AI-driven image solutions in a remote work environment.
Can you work in AI remotely?
Remote AI image jobs are common and often allow for flexible work arrangements, including working from home. These roles typically require skills in AI, machine learning, or image processing, and may involve using tools like Python or cloud platforms. Many companies offer remote positions for AI professionals, provided they have the necessary technical expertise and reliable internet access.
How can I make 2000 a week working from home?
Remote AI image jobs, such as creating or editing AI-generated images, can generate income if you build a strong portfolio and find clients or platforms that pay per project or image. Earning $2000 weekly typically requires multiple projects, consistent work, and skills in AI tools like Midjourney or DALL·E. Developing expertise and marketing your services can help increase your earnings from home.
What are popular job titles related to Remote Ai Image jobs in Remote, OR? For Remote Ai Image jobs in Remote, OR, the most frequently searched job titles are:
What job categories do people searching Remote Ai Image jobs in Remote, OR look for? The top searched job categories for Remote Ai Image jobs in Remote, OR are:
What cities near Remote, OR are hiring for Remote Ai Image jobs? Cities near Remote, OR with the most Remote Ai Image job openings:
Other
Medical, PTO
Posted 27 days ago
Job description
We are looking for a Senior DevOps Developer to help design, build, improve, and operate the tooling and automation that supports our software development and delivery lifecycle.
In this role, you will work closely with DevOps, Architecture, Development, Security, Managed Services, and Services teams to improve CI/CD pipelines, cloud-native deployment workflows, infrastructure automation, observability, security automation, operational feedback loops, and developer experience.
You will be expected to take ownership of technical topics, guide less experienced engineers, and contribute to the evolution of our DevOps and platform engineering practices.
Location:
- Remote - United States / Canada
What You'll Do:
CI/CD, Build & Release Automation
- Design, maintain, and improve CI/CD pipelines using tools such as Jenkins, Bitbucket, Gradle, and related technologies.
- Improve build reliability, pipeline performance, test automation integration, and release automation.
- Support development teams in improving their software delivery workflows.
- Troubleshoot complex build, deployment, and environment issues.
- Contribute to standardization and reuse of pipeline patterns across teams.
- Improve deployment repeatability, traceability, and auditability.
Cloud-Native Platform Engineering
- Support and improve Kubernetes-based deployment and runtime environments.
- Work with containerization technologies such as Docker and Kubernetes.
- Develop and maintain automation for infrastructure, environments, and deployment workflows.
- Contribute to infrastructure-as-code and configuration-as-code practices.
- Support the adoption of GitOps and declarative deployment models.
- Help improve scalability, resilience, and maintainability of cloud-native systems.
- Collaborate with Managed Services and Services teams to ensure platform capabilities are operable and supportable.
DevSecOps & Compliance Automation
- Integrate security controls into CI/CD pipelines and development workflows.
- Support vulnerability scanning, dependency checks, container image scanning, secrets management, and policy enforcement.
- Collaborate with Security and Architecture teams to improve secure software delivery.
- Help ensure pipelines and automation support auditability, traceability, and compliance requirements.
- Promote secure-by-design practices within DevOps and development teams.
Observability, Reliability & Operational Feedback
- Improve observability through metrics, logs, traces, dashboards, and alerting.
- Support incident analysis, root-cause investigation, and operational improvements.
- Work with Managed Services and Services teams to translate operational feedback into better automation, monitoring, deployment practices, and documentation.
- Identify recurring operational issues and automate solutions where possible.
- Contribute to performance, reliability, and scalability improvements.
AI-Enabled Engineering Workflows
- Use AI-assisted tools responsibly to improve DevOps productivity, troubleshooting, documentation, automation, and pipeline analysis.
- Identify practical use cases for AI in CI/CD, DevSecOps, observability, incident analysis, and developer workflows.
- Validate AI-generated code, scripts, configurations, and recommendations through proper engineering review and testing.
- Help define safe usage patterns and guardrails for AI-assisted DevOps work.
- Collaborate with development teams to integrate AI-assisted tools into the software delivery lifecycle.
Who You Are:
- 4+ years of experience in DevOps, platform engineering, infrastructure engineering, or software delivery automation.
- Strong hands-on experience with CI/CD pipelines and automation.
- Experience with Jenkins, Bitbucket, Gradle, Git, and related development tooling.
- Experience with Docker, Kubernetes, and cloud-native deployment patterns.
- Good understanding of infrastructure-as-code, configuration management, and automation.
- Knowledge of GitOps concepts and tools such as ArgoCD, Flux, or similar.
- Understanding of DevSecOps principles and security automation in CI/CD pipelines.
- Experience with observability tools and practices, including logs, metrics, dashboards, and alerting.
- Strong troubleshooting and problem-solving skills.
- Ability to work independently and take ownership of technical topics.
- Good communication skills and ability to collaborate across distributed teams.
- Understanding of AI tools and their application in DevOps, software development, and operational workflows.
- Relevant certifications such as AWS Cloud Practitioner, AWS Certified Solutions Architect, ITIL, CISSP, or CISM.
- Experience with AWS, Azure, GCP, or hybrid cloud environments.
- Experience with Helm, Terraform, Ansible, or similar tooling.
- Experience with Prometheus, Grafana, ELK/OpenSearch, or comparable observability platforms.
- Experience with incident response, production support, managed services enablement, performance tuning, or operational reliability.
- Knowledge of progressive delivery techniques such as feature flags, canary releases, blue-green deployments, and automated rollback.
- Experience with AI-assisted development tools, coding assistants, or AI-based automation in enterprise engineering environments.
Our Values:
- Own It (I do what I say, full accountability for results, finding solutions and Practice ethical and safe behaviors)
- Play as One (Collaborate for a common goal, diverse perspectives. Listen and communicate with respect, support decision for teams' benefits)
- Move Forward (Embrace change, explore opportunities to innovate, feedback and improve performance, Proactive steps to resolve issues and continuous progress).
- Drive Value (Bold choices to maximize value creation, customer deliver exceptional value, add value to all stakeholders, use data to generate crucial insights and outcomes).
What we offer now and in the future:
- Dynamic global organization with a history of innovation and strong product portfolio.
- Challenging environment combined with a supportive management structure.
- Career development and growth.
- Competitive salary and benefit package.
- Friendly work environment surrounded by dedicated and professional colleagues.
Diversity and Inclusion:
At Agfa, our mission at Agfa is to ensure that everyone belongs. We believe that diversity and inclusion of others promotes a greater feeling of belonging and higher levels of engagement. We know that if we work together, we can do amazing things, and that our differences are what make our company, products, and services great.
Compensation: At Agfa HealthCare, we offer a thoughtfully designed benefits package that supports your physical, emotional, and financial wellbeing. As you move through the hiring process, we're happy to provide more details about our compensation programs, including variable and commission compensation opportunities for eligible roles, vacation entitlement, and paid time off.
AI Usage Disclosure: As part of our commitment to transparency, we use artificial intelligence (AI) tools to assist in various stages of our recruitment process, including resume screening, candidate matching, interview scheduling, and communications. These tools are designed to improve efficiency, reduce bias, and enhance candidate experience. All decisions regarding hiring are made by qualified human professionals, and we continuously monitor our AI systems to ensure fairness and compliance with applicable regulations.