1

Generative Ai Developer Jobs in Oregon (NOW HIRING)

Lead AI/ML Engineer

OR · On-site +1

$180K - $230K/yr

Attain Talent is seeking a Lead AI/ML Engineer to lead the design, evaluation, and implementation ... Experience with Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG ...

New

Senior AI Platforms Engineer

OR · On-site +1

$104K - $143K/yr

... Generative AI from "chatting" to "doing." This platform is the intelligent backbone for their semi ... Set the technical direction and engineering standards for high-performance, scalable backend ...

Senior Applied AI Engineer

Hillsboro, OR · On-site

$113K - $156K/yr

If you're passionate about the latest research and cutting-edge technologies shaping generative AI ... Strong Python engineering skills are preferred, with the ability to design, prototype, and ...

... and engineers. WHO WE ARE LOOKING FOR We are looking for a creative, hands-on computational ... You are energized by emerging tools, including Generative AI, and you actively integrate them into ...

Senior AI Product Associate, IT

Portland, OR · On-site +1

$104K - $160K/yr

Work closely with Engineering, tax accountants, and other cross functions to deliver and improve ... Apply generative-AI capabilities relevant to professional services - LLMs, document intelligence ...

... generative AI development * Expert software engineering background (Python or similar) with strong design sensibilities for scalable, maintainable systems * Deep expertise with cloud platforms ...

OR · On-site

We are proud to be creating the future of generative AI and AI agents. Salesforce has launched ... Ability to connect business strategy to execution, partnering closely with product, engineering ...

Senior Gen AI Software Engineer

OR · On-site +1

$122K - $161K/yr

Own generative AI product capabilities end to end, from understanding user workflows and ... Mentor other engineers and help establish shared practices for designing, testing, and operating AI ...

Showing results 41-60

Generative Ai Developer information

See Oregon salary details

$20

$47

$106

How much do generative ai developer jobs pay per hour?

As of Aug 22, 2026, the average hourly pay for generative ai developer in Oregon is $47.88, according to ZipRecruiter salary data. Most workers in this role earn between $24.90 and $57.93 per hour, depending on experience, location, and employer.

What is a generative AI developer?

A Generative AI Developer is a technology professional who specializes in designing, building, and deploying artificial intelligence systems that can create new content, such as text, images, audio, or code. They work with advanced machine learning models, like generative adversarial networks (GANs) or large language models, to enable computers to produce original outputs. These developers often collaborate with data scientists, researchers, and product teams to integrate AI-generated content into software applications and business solutions.

What are the key skills and qualifications needed to thrive as a generative AI developer?

To thrive as a Generative AI Developer, you need strong programming skills (especially in Python), a deep understanding of machine learning concepts, and an advanced degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and experience with cloud platforms or model deployment tools are typically required. Creative problem-solving, adaptability, and effective collaboration are standout soft skills in this evolving field. These abilities are crucial to design, implement, and refine generative models that solve real-world problems and drive innovation.

What are some common challenges faced by generative AI developers when deploying models in production environments?

Generative AI Developers often encounter challenges such as ensuring model reliability, managing computational resource requirements, and addressing ethical considerations like data bias or content safety. Deploying generative models at scale requires robust monitoring to detect unexpected outputs or model drift, and collaboration with data engineers and product teams to optimize performance. Staying up-to-date with evolving frameworks and best practices is essential, as production environments demand both technical rigor and adaptability to new AI advancements.

What is the difference between Generative Ai Developer vs Machine Learning Engineer?

AspectGenerative Ai DeveloperMachine Learning Engineer
CredentialsBachelor's or higher in CS, AI, or related fields; experience with deep learning frameworksBachelor's or higher in CS, Data Science, or related fields; strong programming skills
Work EnvironmentDevelops AI models for content creation, chatbots, and creative applicationsBuilds and deploys ML models for various data-driven solutions across industries
Industry UsageTech, entertainment, marketing, and creative sectorsFinance, healthcare, tech, and e-commerce sectors

While both roles involve AI and machine learning, Generative Ai Developers focus on creating models that generate content, such as images or text, whereas Machine Learning Engineers develop broader ML solutions for diverse applications. The roles often overlap but differ mainly in their specific focus areas and use cases.

How to become a generative AI developer?

To become a generative AI developer, you should have a strong foundation in programming languages like Python, experience with machine learning frameworks such as TensorFlow or PyTorch, and knowledge of neural network architectures like transformers. Gaining expertise in natural language processing and deep learning, along with practical experience through projects or internships, is essential. Certifications in AI or data science can also enhance your qualifications.

What are popular job titles related to Generative Ai Developer jobs in Oregon?

For Generative Ai Developer jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Generative Ai Developer jobs in Oregon look for?

The top searched job categories for Generative Ai Developer jobs in Oregon are:

What cities in Oregon are hiring for Generative Ai Developer jobs?

Cities in Oregon with the most Generative Ai Developer job openings:

Infographic showing various Generative Ai Developer job openings in Oregon as of August 2026, with employment types broken down into 75% Full Time, 23% Part Time, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution, with an average salary of $99,596 per year, or $47.9 per hour.

Cyber AI Governance and Privacy Senior Consultant

Deloitte

Portland, OR

Full-time

Re-posted 26 days ago


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

45th of 151 rated financial services


Job description

We are seeking an AI Governance and Privacy Specialist who can operationalize responsible AI in real systems-especially agentic AI and LLM-enabled applications. This role blends governance and privacy expertise with enough software development fluency to create developer-ready guidance, implement controls-as-code patterns, and stand up measurable evaluation and monitoring workflows.

As a Senior Consultant, you will help clients and internal delivery teams move from AI principles to practices: risk tiering, model and agent inventories, technical guardrails, governance workflows integrated into the SDLC, and evidence artifacts suitable for audits and regulators.

Recruiting for this role ends on 12/31/2026.

Work you'll do

As a Senior Consultant, Strategy, Growth and Transformation on the Cyber team, you will be responsible for:

  • Designing and implementing AI governance operating models, intake workflows, risk tiering, approvals, documentation standards, exception handling, and audit-ready evidence processes for generative AI and agentic AI deployments.
  • Building and maintaining inventories for models, agents, tools, data sources, and integrations, with defined ownership, intended use, risk classification, and change-control requirements.
  • Conducting risk assessments across privacy, security, model risk, and misuse scenarios, including prompt injection, sensitive data exposure, excessive agency, and overreliance, and translating findings into implementable mitigations.
  • Establishing technical control guidance for teams building agentic AI solutions, including human-in-the-loop patterns, tool access controls, retrieval and grounding practices, logging, monitoring, token and data minimization, and incident response playbooks.
  • Integrating governance checkpoints into product and engineering delivery through architecture reviews, release gates, evaluation requirements, documentation automation, evidence capture, dashboards, and cross-functional collaboration with Cybersecurity, Privacy, Legal, Risk, Engineering, and Data Science teams.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The team

You will join a cross-functional group working at the intersection of cyber, privacy, governance, and emerging AI delivery. The team helps organizations scale AI responsibly by combining governance and engineering patterns so teams can innovate faster without compromising trust.

Qualifications

Required:

  • Bachelor's degree or equivalent practical experience.
  • 4+ years of experience in AI governance, data privacy, security risk management, compliance and controls, AI product risk, model risk management, or technology risk consulting.
  • Experience translating policies and regulatory expectations into operational workflows and artifacts, including intake processes, inventories, decision logs, risk registers, responsibility assignment matrices, playbooks, privacy impact assessments, and data protection impact assessments.
  • Experience assessing AI, machine learning, and LLM deployment patterns, including training, retrieval-augmented generation, fine-tuning, tool use, data dependencies, and integration patterns, and defining mitigations for privacy, security, model risk, and misuse.
  • Experience prototyping or automating governance workflows using Python or Structured Query Language and working with continuous integration and continuous deployment pipelines and cloud deployment basics.
  • Ability to travel 0-50%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • Experience in consulting or a Big 4 environment.
  • Experience operationalizing AI governance aligned to the National Institute of Standards and Technology AI Risk Management Framework or ISO/IEC 42001.
  • Experience with generative AI safety and evaluation practices, including prompt injection testing, jailbreak resilience, hallucination measurement, toxicity scoring, harm scoring, and grounding effectiveness.
  • Experience with governance, workflow, or ticketing platforms, including OneTrust and governance, risk, and compliance systems, and integrating those platforms into engineering delivery processes.
  • Certifications such as Certified Information Privacy Professional/United States, Certified Information Privacy Manager, International Association of Privacy Professionals AI Governance Professional, Certified Information Security Manager, or Certified Information Systems Security Professional.
  • Experience in cyber or enterprise security environments, including data security, identity, audit logging, secure software development lifecycle practices, human-in-the-loop escalation pathways, exception handling, and automated safety protocols for autonomous systems.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $105,400 to $207,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

#CyberDTP27

Qualifications:

We are seeking an AI Governance and Privacy Specialist who can operationalize responsible AI in real systems-especially agentic AI and LLM-enabled applications. This role blends governance and privacy expertise with enough software development fluency to create developer-ready guidance, implement controls-as-code patterns, and stand up measurable evaluation and monitoring workflows.

As a Senior Consultant, you will help clients and internal delivery teams move from AI principles to practices: risk tiering, model and agent inventories, technical guardrails, governance workflows integrated into the SDLC, and evidence artifacts suitable for audits and regulators.

Recruiting for this role ends on 12/31/2026.

Work you'll do

As a Senior Consultant, Strategy, Growth and Transformation on the Cyber team, you will be responsible for:

  • Designing and implementing AI governance operating models, intake workflows, risk tiering, approvals, documentation standards, exception handling, and audit-ready evidence processes for generative AI and agentic AI deployments.
  • Building and maintaining inventories for models, agents, tools, data sources, and integrations, with defined ownership, intended use, risk classification, and change-control requirements.
  • Conducting risk assessments across privacy, security, model risk, and misuse scenarios, including prompt injection, sensitive data exposure, excessive agency, and overreliance, and translating findings into implementable mitigations.
  • Establishing technical control guidance for teams building agentic AI solutions, including human-in-the-loop patterns, tool access controls, retrieval and grounding practices, logging, monitoring, token and data minimization, and incident response playbooks.
  • Integrating governance checkpoints into product and engineering delivery through architecture reviews, release gates, evaluation requirements, documentation automation, evidence capture, dashboards, and cross-functional collaboration with Cybersecurity, Privacy, Legal, Risk, Engineering, and Data Science teams.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The team

You will join a cross-functional group working at the intersection of cyber, privacy, governance, and emerging AI delivery. The team helps organizations scale AI responsibly by combining governance and engineering patterns so teams can innovate faster without compromising trust.

Qualifications

Required:

  • Bachelor's degree or equivalent practical experience.
  • 4+ years of experience in AI governance, data privacy, security risk management, compliance and controls, AI product risk, model risk management, or technology risk consulting.
  • Experience translating policies and regulatory expectations into operational workflows and artifacts, including intake processes, inventories, decision logs, risk registers, responsibility assignment matrices, playbooks, privacy impact assessments, and data protection impact assessments.
  • Experience assessing AI, machine learning, and LLM deployment patterns, including training, retrieval-augmented generation, fine-tuning, tool use, data dependencies, and integration patterns, and defining mitigations for privacy, security, model risk, and misuse.
  • Experience prototyping or automating governance workflows using Python or Structured Query Language and working with continuous integration and continuous deployment pipelines and cloud deployment basics.
  • Ability to travel 0-50%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • Experience in consulting or a Big 4 environment.
  • Experience operationalizing AI governance aligned to the National Institute of Standards and Technology AI Risk Management Framework or ISO/IEC 42001.
  • Experience with generative AI safety and evaluation practices, including prompt injection testing, jailbreak resilience, hallucination measurement, toxicity scoring, harm scoring, and grounding effectiveness.
  • Experience with governance, workflow, or ticketing platforms, including OneTrust and governance, risk, and compliance systems, and integrating those platforms into engineering delivery processes.
  • Certifications such as Certified Information Privacy Professional/United States, Certified Information Privacy Manager, International Association of Privacy Professionals AI Governance Professional, Certified Information Security Manager, or Certified Information Systems Security Professional.
  • Experience in cyber or enterprise security environments, including data security, identity, audit logging, secure software development lifecycle practices, human-in-the-loop escalation pathways, exception handling, and automated safety protocols for autonomous systems.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $105,400 to $207,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

#CyberDTP27

Education:Bachelor's DegreeEmployment Type:

What Deloitte employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom