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Prompt Engineering Ai Jobs in Oregon (NOW HIRING)

OR

$179K - $231K/yr

As VP of Engineering, AI Innovations, you will lead the our team of talented software developers ... Practical experience integrating LLMs into production systems, including prompt orchestration ...

$215K - $260K/yr

Prompt engineering and model fine-tuning * Machine learning and deep learning fundamentals ... Shipping AI applications to production environments, and operating them for reliability ...

... prompt engineering, context/state management, and human-in-the-loop patterns. * Systems ... Advanced Agentic AI: Experience building autonomous, multi-step agentic systems utilizing multi ...

... AI use cases, and create solution designs, prototypes, and adoption plans with measurable outcomes. Reusable Solution Engineering * Develop reusable components, APIs, prompt libraries, agent ...

Familiarity with AI/ML tooling, prompt engineering, or integrating LLM-based features into production systems. * Prior experience working in or alongside a platform team supporting multiple internal ...

Develop and implement retrieval-augmented generation (RAG), prompt engineering, semantic search, embeddings, and related techniques to support AI application functionality. * Develop reusable ...

AI Engineer

OR · On-site +1

Experience with Azure AI Studio, Azure Machine Learning, vector databases, and prompt engineering. * Knowledge of NIST AI Risk Management Framework, Responsible AI, and Federal AI governance.

Demonstrated ability to design and build AI-enabled workflows in legal or professional-services settings, including prompt engineering, retrieval-augmented generation (RAG) concepts, and evaluation ...

AI Engineer

Portland, OR · On-site

$50K - $112K/yr

... prompt engineering, LLM evaluation, and fine-tuning, to develop production-ready applications ... for AI projects - Utilizing machine learning libraries like Scikit-Learn for data analysis ...

The Opportunity : The AI Solutions Engineering Delivery Lead will oversee multiple ... and prompt engineering - Proven specialization with major cloud platforms such as AWS, Azure, or ...

Experience with Azure AI Studio, Azure Machine Learning, vector databases, and prompt engineering. * Knowledge of NIST AI Risk Management Framework, Responsible AI, and Federal AI governance.

OR

$126K - $166K/yr

Mentor and support team members on AI tooling, prompt engineering, and AI-assisted workflows. What Skills and Knowledge Will You Bring? Ideal candidates will have: * 5 to 8 years of product ...

Showing results 21-40

Prompt Engineering Ai information

See Oregon salary details

$34.4K

$66.6K

$101K

How much do prompt engineering ai jobs pay per year?

As of Aug 6, 2026, the average yearly pay for prompt engineering ai in Oregon is $66,585.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,700.00 and $76,100.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a prompt engineer in AI, and why are they important?

To thrive as a Prompt Engineer in AI, you need a strong background in computer science, natural language processing, and experience with large language models, often supported by a relevant degree or technical training. Familiarity with AI platforms (such as OpenAI’s GPT), prompt design tools, and programming languages like Python is typically required. Creative problem-solving, attention to detail, and effective communication are crucial soft skills for optimizing prompts and collaborating with cross-functional teams. These skills ensure the development of accurate, efficient, and user-aligned AI outputs in fast-evolving environments.

Is prompt engineering AI a good career?

Prompt engineering AI is a growing field focused on designing effective prompts for AI models like language generators. It requires skills in natural language processing, creativity, and understanding AI behavior, often involving tools like GPT or similar models. As AI adoption increases across industries, demand for prompt engineers is expected to rise, making it a promising career option for those interested in AI and machine learning.

What are some common challenges faced by prompt engineering AI professionals when collaborating with multidisciplinary teams?

Prompt Engineering AI professionals often work closely with data scientists, product managers, and software engineers. One common challenge is translating complex technical requirements from non-technical stakeholders into clear, actionable prompts for AI models. Maintaining effective communication and aligning expectations across teams is crucial, as is ensuring that AI outputs meet both technical and business objectives. Adaptability and a collaborative mindset are essential to navigate differing priorities and continuously optimize AI model performance.

What is the difference between Prompt Engineering Ai vs Data Scientist?

AspectPrompt Engineering AiData Scientist
Required CredentialsKnowledge of AI models, programming, and prompt designDegree in Data Science, Statistics, or related fields
Work EnvironmentTech companies, AI labs, startupsResearch institutions, tech firms, finance, healthcare
Industry UsageAI development, NLP applications, chatbot designData analysis, predictive modeling, data-driven decision making

Prompt Engineering Ai focuses on designing effective prompts for AI models, primarily working with language models and AI tools. Data Scientists analyze data, build models, and generate insights. While both roles require technical skills, Prompt Engineers specialize in AI prompt optimization, whereas Data Scientists work with broader data analysis and statistical methods.

What is a prompt engineer in AI?

A Prompt Engineer in AI is a specialist who designs, tests, and refines the inputs (prompts) given to large language models or generative AI systems to optimize their outputs. They work to understand how different prompt formulations influence AI responses, aiming to make the AI perform specific tasks more accurately and reliably. This role often requires strong analytical skills, creativity, and an understanding of both natural language and the capabilities of AI models. Prompt engineers collaborate with product teams, data scientists, and developers to create efficient workflows and improve user experience with AI tools.

How do I become a prompt engineering AI?

Prompt engineering is a role focused on designing effective prompts for AI language models. To become a prompt engineer, develop skills in natural language processing, understand AI model behavior, and gain experience with tools like GPT or similar platforms; familiarity with programming languages such as Python is also beneficial.
What are popular job titles related to Prompt Engineering Ai jobs in Oregon? For Prompt Engineering Ai jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Prompt Engineering Ai jobs in Oregon look for? The top searched job categories for Prompt Engineering Ai jobs in Oregon are:
Infographic showing various Prompt Engineering Ai job openings in Oregon as of August 2026, with employment types broken down into 76% Full Time, 20% Part Time, 3% Contract, and 1% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $66,585 per year, or $32 per hour.

Vice President, Engineering and AI Innovations

Five9

OR

$179K - $231K/yr

Other

Re-posted 15 days ago


Job description

As VP of Engineering, AI Innovations, you will lead the our team of talented software developers that are responsible for Five9's AI Insights, Agent Assist and GenAI Studio products. These products are in widespread usage today. You will be responsible for directing the next phase of the evolution of these products, significantly expanding their feature sets, improving their capabilities with the latest and greatest in AI technologies, and expanding their reach to more customers with better scale and enterprise capability. You'll take end-to-end ownership, from development through operations.

Required Work Experience:

  • 10+ years experience in engineering management.
  • Experience leading Engineering delivery for Customer Experience AI products, including Agent Assistance, AI Agents, and Conversational Analytics.

Required Skills

  1. Technical Skills

AI / ML / GenAI Expertise

  • Deep understanding of modern AI architectures: LLMs, RAG systems, embeddings, vector databases, multimodal models.
  • Practical experience integrating LLMs into production systems, including prompt orchestration, function calling, structured outputs, and multi-agent workflows.
  • Familiarity with model evaluation, A/B testing, safety techniques, latency/throughput trade-offs, and observability for AI systems.
  • Understanding of fine-tuning, distillation, and model optimization (quantization, pruning, MoE, etc.).
  • Experience with applied ML for NLP, ASR/TTS, NLU, and agent-assist use cases preferred.

Software Engineering Foundations

  • Expert-level proficiency in Java and JVM-based ecosystems.
  • Strong command of modern distributed systems design: microservices, event-driven architectures, concurrency, and fault tolerance.
  • Experience in development and operations of software in public cloud (AWS, GCP, Azure). Nice-to-have: experience with  Google Cloud Platform (GCP)
  • Experience building highly scalable, low-latency systems for enterprise SaaS.
  • Strong understanding of API design (REST, gRPC), SDKs, and integrations with enterprise systems.
  • Proficiency with CI/CD (GitHub Actions, Jenkins, Spinnaker, etc.) and Infrastructure as Code (Terraform).

Operational Excellence

  • Deep knowledge of SRE principles: SLIs/SLOs, incident management, error budgets.
  • Experience running 247 production systems at scale, ideally in multi-region global deployments.
  • Expertise in security, privacy, and compliance relevant to CCaaS environments (SOC2, GDPR, HIPAA, FedRAMP preferred).
  • Solid grasp of network fundamentals (TCP/IP, HTTP/2/3, WebRTC basics, load balancing).
  1. People & Leadership Skills

Engineering Leadership

  • Proven ability to lead, mentor, and grow high-performing engineering teams across multiple disciplines (backend, ML, frontend, DevOps, SRE).
  • Track record of hiring top-tier engineering leaders and technologists.
  • Ability to create a culture of excellence-high velocity, high quality, and accountability.
  • Strong conflict-resolution skills; able to navigate ambiguity and align cross-functional teams.

Collaboration & Communication

  • Exceptional written and verbal communication skills; able to clearly articulate vision, architecture, and trade-offs to both technical and non-technical audiences.
  • Comfortable partnering with Product, Design, Sales Engineering, Customer Success, and Executive Leadership.
  • Ability to inspire teams with a compelling technical vision and roadmap.

Customer-Centric Mindset

  • Deep empathy for customers and agents using Five9's AI products.
  • Experience engaging customers directly to gather insights and validate direction.
  • Ability to translate customer problems into clear technical strategies and roadmaps.
  1. Organizational & Strategic Skills

Vision and Strategy

  • Ability to define and execute the long-range engineering strategy.
  • Strong understanding of the AI competitive landscape; able to guide build-vs-buy decisions and partner evaluations.
  • Experience driving architectural modernization initiatives to scale AI products.

Execution & Delivery

  • Mastery of engineering execution frameworks-OKRs, agile methodologies, metrics-driven management.
  • Ability to balance innovation with reliability, velocity, and long-term maintainability.
  • Skilled in managing large, multi-quarter programs and cross-org dependencies.

Budgeting and Resource Planning

  • Proficiency with capacity planning, headcount allocation, staffing strategy, and forecasting infrastructure costs.
  • Experience negotiating vendor contracts, including AI model providers and cloud services.

Change Management

  • Ability to lead through rapid growth, shifts in technology, and organizational restructuring.
  • Experience merging teams, establishing new engineering sites, and building distributed engineering organizations.