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Ai Reliability Engineer Jobs in Oregon (NOW HIRING)

The AI Solutions Engineer also ensures solutions are developed in accordance with applicable ... AI Monitoring, Security & Reliability * Develop and implement automated evaluation methods and ...

Staff AI Engineer

OR · On-site +1

$177K - $209K/yr

You'll be joining real, in-flight work where reliability, security, and scalability are critical. You'll establish engineering standards, raise the bar on how we build AI systems, and contribute to ...

OR

$193K/yr

Network Engineer, AI Infrastructure Repair Responsibilities: * Define and drive the long-term ... Identify systemic reliability risks in AI network infrastructure and drive cross-functional ...

Cloud Engineer

$55.75 - $74.50/hr

Join our dynamic Cloud Monitoring SRE team where you'll architect and maintain mission-critical ... Evaluate and implement emerging technologies including AI/ML tools where they add operational value

AI Engineer

OR · On-site +1

AI Engineer Role Overview: As an AI Engineer at Particle41 you will design, develop and deploy ... Monitor models/ solutions' performance in production (drift, bias, fairness, reliability) and ...

Cloud Engineer

$55.75 - $74.50/hr

Join our dynamic Cloud Monitoring SRE team where you'll architect and maintain mission-critical ... Evaluate and implement emerging technologies including AI/ML tools where they add operational value

AI tooling - Strong understanding (or 1+ years experience) with MCP, Agentic workflows, SRE workflows e.g AIOps for Anomaly detection, event correlation, alert noise reduction on Prometheus and ...

Staff AI Cloud Engineer

OR · On-site +1

$180K - $225K/yr

Gia is our AI-powered global HR agent that provides HR compliance guidance instantly. Built on over ... Improve CI/CD, testing, observability, reliability, security, and developer experience. * Create ...

Be Seen First

The AI Engineer will play a key role in advancing our artificial intelligence capabilities by ... reliability, and expert service at the forefront of its business model.

Be Seen First

The AI Engineer will play a key role in advancing our artificial intelligence capabilities by ... reliability, and expert service at the forefront of its business model.

... Engineers with a strong passion for Artificial Intelligence (AI) and software development. This ... Troubleshoot, debug, and optimize applications for improved performance and reliability.

New

Troubleshoot production AI issues and continuously improve platform reliability, scalability, security, and user experience. * Document engineering standards, AI platform architecture, evaluation ...

Gia is our AI-powered global HR agent that provides HR compliance guidance instantly. Built on over ... Improve CI/CD, testing, observability, reliability, security, and developer experience. * Create ...

Senior AI Automation Engineer

OR · On-site +1

$103K - $136K/yr

Implement error handling, observability, and reusable design patterns to ensure reliability and ... AI, or software engineering, with 1+ year hands-on in Workato. * Proven expertise with Enterprise ...

AI Engineer

Portland, OR · On-site

$50K - $112K/yr

... AI Engineer, you will be at the forefront of transforming raw data into actionable insights ... reliability, and output groundedness - Optimizing open-weight language models, including LLaMA ...

Integrate LLMs, ML models, and external AI services into existing systems using strong engineering patterns for reliability, observability, and maintainability. * Build workflows that use AI in a ...

Showing results 41-60

Ai Reliability Engineer information

What are the key skills and qualifications needed to thrive as an AI reliability engineer, and why are they important?

To thrive as an AI Reliability Engineer, you need a solid background in computer science or engineering, expertise in AI/ML concepts, and experience with software testing and reliability methodologies. Familiarity with tools like TensorFlow, PyTorch, CI/CD pipelines, and reliability testing frameworks, along with certifications in cloud platforms (e.g., AWS Certified Machine Learning), is highly valuable. Analytical thinking, problem-solving abilities, and strong collaboration skills set top performers apart in this role. These skills ensure robust, dependable AI systems that meet performance standards and maintain trust in critical applications.

What is the difference between Ai Reliability Engineer vs Data Scientist?

AspectAi Reliability EngineerData Scientist
Required CredentialsBachelor's or master's in CS, engineering, or related; certifications in AI/MLBachelor's or master's in CS, statistics, or related; certifications in data analysis or ML
Work EnvironmentTech companies, AI-focused teams, engineering departmentsResearch labs, tech firms, analytics teams
Employer & Industry UsageAI product development, machine learning systems, reliability testingData analysis, predictive modeling, business insights

While both roles involve AI and ML, Ai Reliability Engineers focus on ensuring AI system robustness and uptime, whereas Data Scientists analyze data to generate insights and models. The roles often collaborate but serve different primary functions within AI projects.

What is an AI reliability engineer?

AI Reliability Engineers are professionals responsible for ensuring that artificial intelligence systems function reliably, safely, and effectively over time. They work on monitoring AI models in production, identifying and mitigating potential failures, and improving the robustness of AI systems. Their tasks often include testing, validation, performance monitoring, and implementing best practices for maintaining AI infrastructure. By focusing on reliability, they help organizations deploy AI solutions that are dependable and trustworthy in real-world environments.

What are some common challenges AI reliability engineers face when ensuring model robustness in production environments?

Ai Reliability Engineers often encounter challenges such as monitoring AI model performance for drift or unexpected behavior, managing data quality issues, and implementing automated alerting systems for anomalies. In production, it's crucial to ensure that AI models operate consistently and remain reliable under varying conditions and data inputs. Collaborating closely with data scientists, software engineers, and DevOps teams is essential to address these challenges and to continuously improve model reliability and uptime.

What are popular job titles related to Ai Reliability Engineer jobs in Oregon?

For Ai Reliability Engineer jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Ai Reliability Engineer jobs in Oregon look for?

The top searched job categories for Ai Reliability Engineer jobs in Oregon are:

What cities in Oregon are hiring for Ai Reliability Engineer jobs?

Cities in Oregon with the most Ai Reliability Engineer job openings:

Engineering Manager, Internal Developer Platform

Chainguard

OR • Remote

Full-time

Re-posted 16 days ago


Job description

Engineering Manager, Internal Developer Platform: Builder of Golden Paths

Protecting the software supply chain is one of the most important challenges in technology. At Chainguard, we're building the secure foundation that modern software depends on. Our products help organizations eliminate entire classes of software supply chain risk while enabling developers to move faster, not slower.

We're a remote-first company built by industry experts who believe security, reliability, and developer experience should work together. Our engineering culture emphasizes ownership, craftsmanship, continuous learning, and a relentless focus on customer outcomes.

If you're excited about solving hard technical problems at scale and building teams that deliver exceptional results, we'd love to talk.

The role, in a nutshell: 

Chainguard is hiring an Engineering Manager to lead our Internal Developer Platform team - the group that owns CI/CD, developer tooling, infrastructure automation, and our emerging Agentic Engineering Platform, which lets engineers and AI agents build software together. You'll lead a mature team of senior platform and infrastructure engineers, set the technical roadmap for developer productivity and AI-native engineering, and make sure every engineer at Chainguard can ship software quickly, safely, and with less friction.

About the role: 

Do you believe great infrastructure should disappear into the background? Do you enjoy helping engineers move faster, safer, and with less friction? Do you thrive leading highly experienced engineers who care deeply about reliability, automation, and developer experience?

We are seeking an Engineering Manager to lead our Internal Developer Platform team.

This team owns the systems, tooling, automation, and workflows that power engineering productivity across Chainguard. From CI/CD and developer environments to infrastructure automation and deployment workflows, this team enables every engineer in the company to deliver software quickly and safely.

As Chainguard continues its evolution into an AI-first engineering organization, this team is responsible for building the platforms, golden paths, and guardrails that allow engineers and AI agents to collaborate throughout the software development lifecycle.

Reporting to the Senior Director of Platform & Integrations, you will lead a mature, highly skilled team of platform and infrastructure engineers focused on delivering world-class developer experience.

This role is ideal for a technical leader who understands modern platform engineering, has strong SRE instincts, and enjoys helping senior engineers operate at their highest level.

You Will Be Responsible For: 

Developer Experience Making engineers more productive every day by continuously improving the systems, workflows, tooling, and AI capabilities that support software development across Chainguard.

Golden Paths Creating opinionated, self-service platform capabilities and AI-native engineering workflows that allow engineers to focus on solving customer problems rather than managing infrastructure or repetitive engineering tasks.

CI/CD Excellence Owning and evolving our software delivery systems, ensuring builds, testing, releases, and deployments are fast, reliable, secure, and scalable.

Platform Reliability Driving operational excellence through SLOs, observability, automation, capacity planning, and continuous improvement.

Agentic Engineering Platform Own and evolve Chainguard's Agentic Engineering Platform, enabling engineers to leverage AI across the software development lifecycle. Build the shared infrastructure, tooling, context management, evaluation frameworks, and guardrails that make AI-assisted engineering secure, scalable, and effective.

Team Leadership Leading a highly experienced team of senior engineers. Removing obstacles, creating clarity, and fostering an environment where engineers can do exceptional work.

Infrastructure Automation Advancing Infrastructure as Code, GitOps, and platform automation initiatives that improve consistency and reduce operational burden.

Technical Strategy Define and execute the roadmap for both the Internal Developer Platform and the Agentic Engineering Platform, balancing short-term engineering needs with long-term investments in developer productivity, AI capabilities, reliability, and security.

Cross-Functional Collaboration Partnering closely with application teams, security teams, and engineering leadership to understand developer needs and prioritize platform investments.

Incident Leadership Participating in operational reviews, postmortems, and continuous improvement efforts while promoting a strong reliability culture.

AI Engineering Enablement Drive the adoption of AI across Engineering. Partner with engineering teams to identify opportunities, establish best practices, and continuously improve developer productivity through AI.

Qualifications: Engineering Leadership
  • Experience managing software, infrastructure, platform, or SRE teams.
  • Proven success leading highly experienced engineers.
  • Strong coaching, communication, and organizational skills.
  • Champion AI adoption across Engineering by leading through example. Engineering leaders are expected to actively use AI in their own workflows and help their teams continuously improve how they leverage AI to deliver better software. We believe in the Token Rule for Engineering Leadership: managers should remain hands-on enough with AI tooling to effectively coach their teams while focusing on maximizing the organization's overall productivity rather than their own individual output.
Platform Engineering
  • Experience building and operating Internal Developer Platforms, Developer Portals, or similar engineering productivity systems.
  • Deep understanding of platform engineering principles and developer experience best practices.
AI-First Engineering
  • Experience introducing AI-assisted software development into engineering organizations.
  • Familiarity with coding agents such as Claude Code, Codex, Cursor, or similar tools.
  • Understanding of context engineering, evaluation frameworks, and operating AI-assisted development workflows.
  • Passion for improving engineering productivity through AI.
SRE & Operations
  • Strong background in Site Reliability Engineering, Production Engineering, DevOps, or Platform Engineering.
  • Experience with incident management, SLOs, observability, capacity planning, and operational excellence.
Technical Experience
  • Strong Kubernetes and cloud infrastructure experience.
  • Familiarity with infrastructure automation and GitOps workflows.
  • Experience operating production services at scale.
GitHub & GitLab Expertise
  • Deep experience with GitHub and/or GitLab administration and workflows.
  • Strong understanding of CI/CD systems, repository management, developer workflows, and software supply chain best practices.
Communication & Collaboration
  • Exceptional ability to work across organizational boundaries.
  • Strong written communication and documentation skills.
  • Ability to influence without authority and build consensus across diverse teams.
Bonus Points
  • Experience in Linux distros
  • Experience in security-focused organizations.
  • Experience supporting large-scale Kubernetes environments.
  • Familiarity with software supply chain security and secure software delivery practices.
What Success Looks Like
  • Our engineers love using the platform.
  • Other engineering teams move faster because of your work.
  • Reliability improves, friction disappears, and developer productivity increases.
  • Engineers spend less time on repetitive work and more time solving customer problems through effective collaboration with AI.
  • The Agentic Engineering Platform becomes a strategic advantage that accelerates software delivery while maintaining Chainguard's high standards for security, reliability, and software supply chain integrity.
  • Engineering leaders actively model AI-native engineering practices and continuously raise the organization's ability to leverage AI effectively.
  • The Internal Developer Platform becomes one of Chainguard's strategic advantages, enabling engineers to focus on building products rather than fighting infrastructure.
  • And when something breaks, your team already has the automation, observability, and operational rigor to recover quickly and learn from it.