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Llm Prompt Engineer Jobs in Portland, OR (NOW HIRING)

Boomerang Healthcare

AI Full Stack Developer

Portland, OR · On-site

$125K - $160K/yr

LLM prompt engineering & optimization -- Author, test, version, and maintain prompts for BHC-specific use cases including denial review, authorization summarization, clinical documentation assistance ...

Deloitte

AI Engineer Consultant

Portland, OR · Hybrid

We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that ... prompt/context patterns. * Implement LLM application patterns including RAG, document ingestion ...

Pwc

AI Engineer

Portland, OR

$50K - $112K/yr

... prompt engineering, LLM evaluation, and fine-tuning, to develop production-ready applications powered by foundation models - Developing automated evaluation frameworks, including LLM-as-judge ...

Pwc

GenAI Python Systems Engineer-Manager

Portland, OR · On-site

$99K - $232K/yr

... prompt engineering for LLM optimization - Implementing data integration solutions using AWS, Azure, GCP - Utilizing AWS CloudFormation, Azure Resource Manager, Terraform - Building and deploying ...

Pwc

GenAI Python Systems Engineer-Director

Portland, OR · On-site

$155K - $410K/yr

... prompt engineering for LLM outputs - Developing scalable data storage solutions using cloud services - Designing and managing data warehouses and data lakes - Implementing IAM roles and policies for ...

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How much do llm prompt engineer jobs pay per hour?

As of Aug 29, 2026, the average hourly pay for llm prompt engineer in Portland, OR is $61.74, according to ZipRecruiter salary data. Most workers in this role earn between $48.17 and $75.48 per hour, depending on experience, location, and employer.

What is an LLM Prompt Engineer?

An LLM Prompt Engineer is a professional who specializes in designing, testing, and optimizing prompts for large language models (LLMs) such as GPT-4. Their role involves crafting effective instructions and queries to guide the model's output for specific applications, ensuring accuracy, relevance, and reliability. They may also analyze model behavior, implement prompt-based workflows, and collaborate with developers to integrate LLMs into products or services. The goal is to maximize the performance and efficiency of language models in various real-world contexts.

What are the key skills and qualifications needed to thrive as an LLM Prompt Engineer?

To thrive as an LLM Prompt Engineer, you need a deep understanding of natural language processing, prompt engineering strategies, and proficiency in programming languages such as Python, often supported by a degree in computer science or a related field. Familiarity with machine learning frameworks (like TensorFlow or PyTorch), large language model APIs, and version control systems is typically required. Strong analytical thinking, creativity, and effective communication are crucial soft skills for crafting precise prompts and collaborating with cross-functional teams. These skills ensure the development of effective, ethical, and high-performing AI-powered solutions that meet diverse user needs.

What are some common challenges faced by LLM Prompt Engineers when designing effective prompts for large language models?

LLM Prompt Engineers often encounter challenges such as ensuring prompts are both clear and unambiguous to elicit accurate model responses, as well as avoiding bias or unintended outputs. Balancing creativity and specificity in prompt design can be tricky, especially when tailoring prompts for diverse user intents or specialized domains. Additionally, prompt engineers must frequently iterate and test their prompts, collaborating closely with data scientists and product teams to continually refine them based on observed model behavior and user feedback.

What is the difference between Llm Prompt Engineer vs Data Scientist?

AspectLlm Prompt EngineerData Scientist
Required CredentialsBachelor's in CS, AI, or related fields; familiarity with NLP and AI toolsBachelor's or higher in CS, Statistics, or related fields; strong programming and statistical skills
Work EnvironmentAI labs, tech companies, startups focusing on NLP and AI modelsData analysis, modeling, and visualization in various industries like finance, healthcare, tech
Employer & Industry UsagePrimarily in AI development, NLP projects, and machine learning teamsAcross industries for data analysis, predictive modeling, and decision support

While both roles involve working with data and AI, Llm Prompt Engineers focus on designing prompts for language models, whereas Data Scientists analyze data to derive insights. The roles share similar educational backgrounds and work environments but differ in their core tasks and industry applications.

Are AI prompt engineers in demand?

AI prompt engineers are increasingly in demand as organizations seek to optimize interactions with large language models and AI systems. The role requires skills in natural language processing, prompt design, and familiarity with AI tools, with job growth driven by expanding AI applications across industries.

What are popular job titles related to Llm Prompt Engineer jobs in Portland, OR?

For Llm Prompt Engineer jobs in Portland, OR, the most frequently searched job titles are:

What job categories do people searching Llm Prompt Engineer jobs in Portland, OR look for?

The top searched job categories for Llm Prompt Engineer jobs in Portland, OR are:

Llm Prompt Engineer jobs near you

AI Full Stack Developer

Boomerang Healthcare

Portland, OR • On-site

$125K - $160K/yr

Full-time

Posted 10 days ago

Job description



BHC has defined its AI use case priorities, chosen its LLM platform, and built the data foundation. What it needs now is someone to turn those ingredients into tools that actually get used — by the RCM coordinator triaging a denial, the billing lead reviewing an authorization, or the clinical ops team managing a workflow exception. The AI Fullstack Developer designs, builds, and iterates on internal AI-powered applications using Retool as the primary delivery platform and enterprise LLM APIs (Claude Enterprise, AWS Bedrock, or equivalent) as the intelligence layer. This is a senior individual contributor role reporting to the Director of Data & AI, with direct daily exposure to every operational workflow in the organization.  

 *This is a hybrid position


      What you will do: 


  • Internal AI tool delivery — Design, build, and maintain a suite of internal tools on Retool — from initial prototype to production deployment. Own the full stack: Retool application, Python backend API, and LLM integration layer. First-year focus is RCM, billing, and clinical operations workflows.
  • LLM prompt engineering & optimization — Author, test, version, and maintain prompts for BHC-specific use cases including denial review, authorization summarization, clinical documentation assistance, and RCM workflow triage. Own the prompt library and its evaluation framework.
  • Data layer integration — Connect internal tools to BHC’s Snowflake and dbt data layer, source system APIs (IMS and related), and operational data feeds. Know where the data lives, how to query it efficiently, and how to surface it safely inside a tool.
  • Application-layer PHI controls — Implement and maintain HIPAA-compliant data handling within the application layer: PHI masking, role-based access, audit logging, and data minimization patterns. Own application-level security in coordination with the Director and legal/compliance.
  • User experience for operational staff — Design interfaces for RCM coordinators, billing staff, and clinical ops users working under time pressure — not for engineers or analysts exploring dashboards. Understand what ‘usable’ means to someone processing 40 authorizations a day.
  • Iteration & adoption — Instrument tools for usage tracking, gather structured feedback from operational teams, and ship improvements regularly. Measure adoption and outcomes, not just deployment.
  • Documentation & tooling standards — Maintain clear documentation of APIs, prompt patterns, integration architecture, and reusable Retool components. Build the pattern library that makes the second tool faster to ship than the first.


    Qualifications: 

  • Strong Python development experience — REST API design and development (FastAPI preferred), async patterns, data validation, and production error handling.
  • Hands-on Retool experience at a production level — multi-step workflows, role-based access, API resource configuration, custom components, and Retool-native automation. Equivalent deep experience with a comparable low-code internal tooling platform considered.
  • Direct LLM API integration experience — prompt engineering, tool/function calling, RAG implementation, context window management, and response evaluation. Experience with Claude Enterprise, AWS Bedrock, OpenAI, or similar platforms.
  • Experience building HIPAA-compliant applications — PHI handling, audit logging, role-based access controls, and data minimization at the application layer. Understanding of what HIPAA requires at runtime, not just policy.
  • Practical SQL proficiency — able to query Snowflake or equivalent columnar stores; working familiarity with dbt models as data sources is a meaningful plus.
  • Ability to translate operational workflows into application requirements with minimal guidance — comfortable interviewing an RCM coordinator, identifying the actual pain point, and building against it rather than against a spec.
  • Healthcare, RCM, or billing domain experience is preferred. Exceptionally strong technical candidates without healthcare background will be considered if they demonstrate fast domain ramp.


Compensation Range: 

$125,000 - $160,000 Annually

All compensation ranges are posted based on internal equity, job requirements, experience, and geographical locations.


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