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Remote Prompt Engineering Jobs in Oregon (NOW HIRING)

Expertise in prompt engineering and AI-assisted development as a daily practice - Claude Code ... While we will consider remote applicants on a case-by-case basis, local presence is strongly valued ...

Fully Remote Reports To: Business Transformation Lead Expion Health is building the future of ... Develop prompt engineering frameworks and reusable AI workflow templates that AI Champions and ...

Principal Full Stack Engineer

OR · On-site +1

$134K - $180K/yr

Hands-on experience working with LLMs and prompt engineering. You use AI to bridge gaps and ... Own a piece of the company's success. * 100% Remote: Work from anywhere in the US. * 100% Employer ...

AI Solutions Manager

OR · On-site +1

$130K - $150K/yr

Fully Remote Reports To: Business Transformation Lead Expion Health is building the future of ... Develop prompt engineering frameworks and reusable AI workflow templates that AI Champions and ...

Hybrid (+50% Remote) - Remote 60% / Onsite 40% EXPECTED PAY RANGE: Data Scientist I: $99,608 - $136 ... RAG pipelines * Prompt engineering and evaluation frameworks * Familiarity with: * Distributed ...

Principal Software Engineer - Hosting

OR · On-site +1

$134K - $180K/yr

Pantheon is a vibrant, remote-forward team of experts who care deeply about their craft and results ... prompt engineering, and RAG - with the ability to prototype and ship AI features to production

Senior Forward Deployed Engineer (AI Agent)

OR · On-site +1

$104K - $143K/yr

Hands-on experience with large language models (LLMs), and prompt engineering techniques are ... Remote work setup budget to help you create a productive home office * Monthly wellness and ...

Senior Software Engineer -GCP

OR · On-site +1

$122K - $161K/yr

Familiarity with prompt engineering, agent context design, or structured documentation practices ... For positions with Remote-US locations, the actual salary range for the position may differ based ...

Senior Software Engineer -GCP

Salem, OR · On-site +1

$123K - $162K/yr

Familiarity with prompt engineering, agent context design, or structured documentation practices ... For positions with Remote-US locations, the actual salary range for the position may differ based ...

Revenue Operations Lead - 100% Remote

OR · On-site +1

$140K - $170K/yr

... including prompt engineering, agent design, and integrating LLMs into business workflows ... We're a lean, fully remote team of around 50 people in the middle of an ambitious chapter: evolving ...

This customer-facing role blends product thinking, prompt engineering, data-driven insights, and ... Remote work setup budget to help you create a productive home office * Monthly wellness and ...

Developers, DevOps engineers, and platform teams use Upsun to build, ship, and scale confidently ... Upsunners are a remote, global workforce, and we thrive in a multicultural team. We are committed ...

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Remote Prompt Engineering information

See Oregon salary details

$18

$34

$50

How much do remote prompt engineering jobs pay per hour?

As of Jun 10, 2026, the average hourly pay for remote prompt engineering in Oregon is $34.95, according to ZipRecruiter salary data. Most workers in this role earn between $27.98 and $40.43 per hour, depending on experience, location, and employer.

How can I make 2000 a week working from home?

Remote prompt engineering is a freelance or contract role that can generate significant income if you have strong skills in AI, natural language processing, and prompt design. Earning $2000 weekly typically requires multiple clients, high-quality work, and efficient time management, often involving project-based tasks or retainer agreements. Building a portfolio and gaining experience with tools like GPT models can help increase earning potential.

What is the difference between Remote Prompt Engineering vs Remote Data Annotation Specialist?

AspectRemote Prompt EngineeringRemote Data Annotation Specialist
Required CredentialsBasic understanding of AI, NLP, and scripting skillsAttention to detail, familiarity with annotation tools, no formal certifications required
Work EnvironmentCollaborative with AI/ML teams, remote setupIndependent annotation tasks, remote or on-site
Industry UsageAI development, NLP projects, machine learningData labeling for AI training datasets
Search & Comparison IntentUnderstanding roles in AI development, job requirementsData labeling jobs, annotation tasks, related roles

Remote Prompt Engineering involves designing and refining prompts for AI models, requiring some technical skills and collaboration with AI teams. In contrast, Remote Data Annotation Specialists focus on labeling data to train AI systems, emphasizing attention to detail. Both roles are essential in AI development but differ in skills and daily tasks.

What are some common challenges faced by remote prompt engineers, and how can they be addressed?

Remote prompt engineers often face challenges related to communication and collaboration, especially when working across time zones and with interdisciplinary teams. Staying updated on rapidly evolving AI technologies and understanding nuanced user requirements can also be demanding. To address these, prompt engineers can leverage collaborative tools, maintain clear documentation, and participate in regular team syncs. Building a habit of continuous learning and engaging in knowledge-sharing sessions helps keep skills relevant and fosters a sense of connection despite remote work.

What are the key skills and qualifications needed to thrive as a Remote Prompt Engineer, and why are they important?

To thrive as a Remote Prompt Engineer, you need a strong background in natural language processing, programming (often Python), and an understanding of AI/ML concepts, typically supported by a relevant degree or industry experience. Familiarity with large language models (like OpenAI's GPT), prompt optimization tools, and version control systems such as Git is common. Creativity, problem-solving, and strong written communication are vital soft skills for designing effective prompts and collaborating remotely. These skills ensure the development of high-performing AI solutions and seamless teamwork in distributed environments.

What is remote prompt engineering?

Remote prompt engineering is the practice of designing and refining prompts for AI language models, such as ChatGPT, while working from a remote location. Prompt engineers craft instructions or questions to optimize the model’s responses for specific tasks or applications. This role typically involves understanding both the capabilities and limitations of AI systems, as well as the needs of end users or clients. Remote prompt engineers collaborate online with teams and may work for tech companies, research organizations, or as independent contractors.
What are the most commonly searched types of Prompt Engineering jobs in Oregon? The most popular types of Prompt Engineering jobs in Oregon are:
What are popular job titles related to Remote Prompt Engineering jobs in Oregon? For Remote Prompt Engineering jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Remote Prompt Engineering jobs in Oregon look for? The top searched job categories for Remote Prompt Engineering jobs in Oregon are:
What cities in Oregon are hiring for Remote Prompt Engineering jobs? Cities in Oregon with the most Remote Prompt Engineering job openings:
Staff AI Engineer - Grafana Ops, AI/ML | USA | Remote

Staff AI Engineer - Grafana Ops, AI/ML | USA | Remote

Grafana Labs

OR • Remote

Other

Posted 12 days ago


Job description

This is a remote opportunity and we would be interested in applicants from USA time zones only at this time.

Staff AI Engineer 

The Opportunity: 

At Grafana, we build observability tools that help users understand, respond to, and improve their systems - regardless of scale, complexity, or tech stack. The Grafana AI teams play a key role in this mission by helping users make sense of complex observability data through AI-driven features. These capabilities reduce toil, lower the barrier of domain expertise, and surface meaningful signals from noisy environments. 

What makes our team different is how we work: we operate with a high degree of autonomy and ownership, both as individuals and as a team. Engineers are empowered to make decisions, move quickly, and validate ideas early - while being supported by a deeply collaborative culture that values curiosity, feedback, and cross-functional partnership.

We're looking for an AI Software Engineer with a strong software engineering background, a quick iteration mindset, and a passion for experimentation - balanced by a focus on shipping and scaling impactful features that deliver value to users. You'll work closely with cross-functional teams to develop, test, and ship AI-powered features that contribute to improving infrastructure and observability quality through automation, while also expanding the capabilities of AI agents across the observability stack to assist users with incident response. As the team matures, there's a broad opportunity to expand or redefine this role based on impact and initiative.

What You'll Be Doing:

  • Build and deliver AI solutions: Take ownership of developing high-performance AI features to help users detect, triage, and resolve incidents using observability data and tools. 
  • Rapid experimentation and iteration: Implement a highly iterative process where you quickly prototype, test, and validate with real users, including shipping and evolving LLM- or agent-powered workflows for incident lifecycle management and automated analysis tasks.
  • Collaborate cross-functionally: Work with data analysts, product managers, and designers to shape AI-driven product features, including integration of agentic components with internal tools, alerting systems, runbooks, and developer workflows. 
  • Utilize AI tools effectively: Use AI and automation tools to enhance both product functionality and your own development workflows. 
  • Effective communication: You'll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams.
  • Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows. 

We invest heavily in developer productivity. You can use modern AI coding assistants as part of your daily workflow (your choice of tools, within security guidelines), backed by a company-funded usage budget so you can iterate quickly without unnecessary friction.

We encourage pragmatic AI-assisted development: faster prototyping, test generation, refactors, documentation, and incident follow-ups-always paired with strong code review and quality standards.

You'll also have access to frontier models (e.g., GPT-Codex 5/3, Claude Opus 4.6, Gemini 3 Pro).

What Makes You a Great Fit:

  • Strong engineering skills: Solid experience building production software systems (backend and / or full stack). You're a self-starter, capable of tackling complex engineering problems with minimal supervision.
  • AI experience with a practical mindset: You're familiar with AI technologies and frameworks, and you focus on delivering high-quality solutions that work in the real world, not just in theory. 
  • Quick iteration and experimentation: You're comfortable releasing prototypes, collecting feedback, and iterating with a pragmatic mindset.
  • Proven initiative: You take ownership and drive projects forward, pushing boundaries to find the most impactful solutions. You can deal with ambiguity and are able to define scope where things are loosely defined. 
  • Collaborative attitude: You communicate effectively with peers, product managers, and designers. You're open to feedback, and you bring a solutions-oriented mindset to the table.

Requirements: 

  • Experience with LLMs, prompt engineering, and building applications powered by GenAI.
  • Proven track record of delivering software that made it into production and is actively used by users. 
  • Exposure to working in cloud-native environments (e.g., AWS, GCP, Azure).
  • Experience using observability tools to understand and troubleshoot system behavior.

Bonus Points For:

  • Experience building or working with agent frameworks or multiagent workflows.
  • Experience with infrastructure / devops related tooling: Kubernetes, Docker, Terraform or similar for deployments.
  • Familiarity with model fine-tuning techniques.
  • Experience building observability tooling.

Compensation & Rewards:

In the United States, the Base compensation range for this role is USD 174,986 - USD 220,000. Actual compensation may vary based on level, experience, and skillset as assessed in the interview process. Benefits include equity, bonus (if applicable) and other benefits listed here.

All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana Labs' success. We believe in shared outcomes-RSUs help us stay aligned and invested as we scale globally.