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Ai Automation Testing Jobs in Oregon (NOW HIRING)

Senior AI Automation Engineer

OR · On-site +1

$103K - $136K/yr

About the Role We are seeking a hands-on AI & Automation Engineer to design, build, and optimize ... A/B testing agent versions, model comparisons. Programming for Automation * Write modular, reusable ...

We're looking for a Software Engineer to join our AI/Automation team and contribute to the design ... testing. This role is hands-on. You'll be writing code, building features, integrating AI ...

The Opportunity Grafana Labs is seeking a Staff Engineer (AI & Automation) to own the AI agent ... testing, deployment, and ongoing operation * Build modular, composable agentic systems using ...

Test Automation Engineer

Hood River, OR · On-site

$48 - $63.50/hr

Test Automation & Tooling * Build and maintain automated regression and integration tests ... AI-Assisted Testing * Apply AI where it improves validation: * UI testing (e.g., Playwright). * Log ...

Test Automation Engineer

Hood River, OR · On-site

$130K - $180K/yr

Test Automation & Tooling * Build and maintain automated regression and integration tests ... AI-Assisted Testing * Apply AI where it improves validation: * UI testing (e.g., Playwright). * Log ...

Test Automation Engineer

Hood River, OR

$48 - $63.50/hr

AI-Assisted Testing * Apply AI where it improves validation: * UI testing (e.g., Playwright). * Log ... Experience building test automation, tools, or frameworks. * Proficient in Python and Linux ...

AI Engineer, Sr

Newberg, OR · On-site

$109K - $150K/yr

Python for building AI models, automation, and production services • SQL for working with ... and testing expertise, including prompt testing, experimentation and A/B testing, system ...

AI Engineer, Sr

Newberg, OR · On-site

$109K - $150K/yr

This role focuses on delivering practical AI solutions that drive automation, improve decision ... Applied model evaluation and testing expertise, including prompt testing, experimentation and A/B ...

AI Engineer, Sr

Newberg, OR · On-site

$109K - $150K/yr

This role focuses on delivering practical AI solutions that drive automation, improve decision ... Applied model evaluation and testing expertise, including prompt testing, experimentation and A/B ...

Develop reusable AI harnesses to automate testing, prompt evaluation, model benchmarking ... Implement CI/CD pipelines and infrastructure automation supporting enterprise AI development and ...

AI Engineer

OR · On-site +1

Build AI Copilots, AI Agents, and Retrieval-Augmented Generation (RAG) solutions to improve software engineering, testing, documentation, and operational workflows. * Develop intelligent automation ...

Senior Developer RPA

Portland, OR

$57.75 - $76.25/hr

... access, and AI-enabled automation opportunities such as AWS Bedrock integrations. Main ... Own quality across the delivery lifecycle, including testing, deployment readiness, defect ...

Senior Engineer, Test Automation

OR · On-site +1

$130K - $180K/yr

Evaluate and apply AI-assisted testing techniques, such as LLM-based test generation and ... Strong proficiency with Playwright and experience building automation frameworks that are reliable ...

Senior Developer RPA

Portland, OR

$57.75 - $76.25/hr

... access, and AI-enabled automation opportunities such as AWS Bedrock integrations. Main ... Own quality across the delivery lifecycle, including testing, deployment readiness, defect ...

Build AI Copilots, AI Agents, and Retrieval-Augmented Generation (RAG) solutions to improve software engineering, testing, documentation, and operational workflows. * Develop intelligent automation ...

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Ai Automation Testing information

What are some common challenges faced by AI automation testing professionals when validating machine learning models?

AI Automation Testing professionals often encounter challenges such as ensuring that test cases comprehensively cover the unique behaviors of machine learning models, dealing with non-deterministic outputs, and handling large datasets efficiently. It's also common to face difficulties in setting up reliable test environments that simulate real-world data scenarios. Collaboration with data scientists and developers is crucial to define meaningful metrics and effectively interpret test results, ensuring the AI system meets both functional and ethical standards.

What is AI automation testing?

AI automation testing refers to the use of artificial intelligence technologies to automate the process of testing software applications. This approach enhances traditional automated testing by using machine learning and data analysis to identify test cases, detect defects, and optimize test coverage. AI-driven testing tools can adapt to changes in the application, reduce manual effort, and improve the accuracy and speed of testing processes. As a result, organizations can deliver higher-quality software more efficiently.

What are the key skills and qualifications needed to thrive as an AI automation testing professional?

To thrive as an AI Automation Testing professional, you need a solid understanding of software testing principles, programming languages (such as Python or Java), and AI/ML concepts, often supported by a degree in computer science or a related field. Familiarity with automation tools like Selenium, Appium, and AI-powered testing frameworks, as well as certifications like ISTQB, is highly valued. Strong analytical thinking, attention to detail, and effective communication skills help professionals excel in diagnosing issues and collaborating with development teams. These skills ensure the delivery of robust, efficient, and reliable AI-driven software products in a competitive technology landscape.

What is the difference between Ai Automation Testing vs Software Test Engineer?

AspectAi Automation TestingSoftware Test Engineer
Required CredentialsCertifications in AI, automation tools, programming languagesSoftware testing certifications (ISTQB, CSTE), programming skills
Work EnvironmentFocus on automation frameworks, AI integration, scriptingManual and automated testing, test case design, bug tracking
Employer & Industry UsageTech companies, AI-driven projects, software development firmsSoftware development companies, IT departments, QA teams

Ai Automation Testing and Software Test Engineer roles overlap in testing skills and programming knowledge. However, Ai Automation Testing emphasizes AI integration and automation frameworks, while Software Test Engineers focus more on manual testing, test case creation, and bug identification. Both roles are essential in software quality assurance but serve different aspects of the testing process.

What are popular job titles related to Ai Automation Testing jobs in Oregon?

For Ai Automation Testing jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Ai Automation Testing jobs in Oregon look for?

The top searched job categories for Ai Automation Testing jobs in Oregon are:

What cities in Oregon are hiring for Ai Automation Testing jobs?

Cities in Oregon with the most Ai Automation Testing job openings:

Infographic showing various Ai Automation Testing job openings in Oregon as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution.

Senior AI Automation Engineer

Tebra

OR • On-site, Remote

$103K - $136K/yr

Full-time

Re-posted 14 days ago


Job description

About the Role

We are seeking a hands-on AI & Automation Engineer to design, build, and optimize integrations, automations, and advanced AI workflows, including agentic architecture, that power our enterprise business operations. You'll own the Workato automation stack, engineer scalable AI workflows on top of core platforms (Salesforce, NetSuite, Snowflake, Slack), and implement agentic capabilities that allow systems to act as intelligent tools, reducing manual work and accelerating insights.

This role requires deep technical execution skills in integration development, agentic system design, and programming, combined with a practical understanding of AI workflows. You will collaborate directly with stakeholders to translate business needs into scalable, automated solutions and deliver measurable improvements in system efficiency and operational performance.

Your Area of Focus

Integration & Automation Development

    • Design, build, and maintain Workato recipes, connectors, and orchestrations for Salesforce, NetSuite, Slack, and Snowflake.
    • Implement error handling, observability, and reusable design patterns to ensure reliability and scalability.

Agentic System Design

    • Architect multi-agent systems: tool selection, planning loops, state management, human-in-the-loop Checkpoints.
    • Partner with stakeholders to design corporate systems (Salesforce, NetSuite, Snowflake, Slack, etc) as agent-callable tools, not just data sources.
    • Build guardrails, fallbacks and error recovery for non-deterministic workflows.

Data/RAG Pipeline Design & Management

    • Design and automate data flow processes to support AI retrieval (RAG) and insights generation across core enterprise platforms.
    • Build evaluation into every system to ensure high quality results, considering precision, answer faithfulness, latency, and cost.
    • Own the Retrieval-Augmented Generation (RAG) lifecycle end-to-end, including ingestion, chunking strategy, embeddings, vector storage, and reranking.
    • Implement data quality checks and architectural safeguards to ensure trusted, high-fidelity datasets for AI agents.

AI Operations

    • Production observability: prompt/response tracing, cost monitoring, eval dashboards.
    • Document agent behavior, decision logic and failure modes.
    • A/B testing agent versions, model comparisons.

Programming for Automation

    • Write modular, reusable scripts in Python, Ruby, SQL, or JavaScript to support integration, data transformation, and automation tasks.

Governance & Documentation

    • Apply data governance practices for lineage, security, and retention.
    • Maintain technical documentation, diagrams, and version control via GitHub, Confluence, and Jira.
Your Professional Qualifications
  • 5+ years of experience in integration, automation, AI, or software engineering, with 1+ year hands-on in Workato.
  • Proven expertise with Enterprise iPaaS required (Workato, Mulesoft, or similar).
  • Deep proficiency in designing, implementing, and architecting complex AI workflows and integrations across core platforms (Salesforce, NetSuite, Slack, and Snowflake).
  • Hands-on technical background in programming (Python, Ruby, or similar), leveraging APIs to build and maintain scalable, high-fidelity enterprise systems.
  • Experience using vector databases such as Pinecone, Snowflake Cortex Search, and pgvector for Retrieval-Augmented Generation (RAG).
  • Experience with AI/ML concepts and implementing agentic architecture and AI workflows in enterprise environments.
  • Experience with Cloud Platforms such as GCP or AWS preferred.
  • Experience with GitHub for version control, Jira for work tracking, and Confluence/Lucid for documentation.
  • Strong problem-solving, critical thinking, and ability to execute under minimal supervision.
  • Motivated to learn new technologies and develop new skills.
  • Track record of introducing innovation in automation and AI while maintaining governance and system reliability.
  • Workato Automation Pro , Foundations or SnowPro certifications preferred.

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