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Ai Reliability Engineer Jobs in Oregon (NOW HIRING)

Vice President, Engineering and AI Innovations

OR ยท On-site +1

$179K - $231K/yr

As VP of Engineering, AI Innovations, you will lead the our team of talented software developers ... Deep knowledge of SRE principles: SLIs/SLOs, incident management, error budgets. * Experience ...

... AI agents, and serves the Financial Intelligence Graph to Fortune 500 customers who expect ... Strong SRE instincts: you think in terms of SLOs, capacity planning, incident response, and ...

Principal Infrastructure Security Engineer

OR ยท On-site +1

$142K/yr

Our team partners closely with platform, infrastructure, SRE, product engineering, risk, and ... Partner with engineering teams to improve the security of AI-assisted developer workflows and GenAI ...

... AI/ML), Platform, Delivery, Sustaining, and Security to ensure the platform meets reliability ... Mentor and unblock other engineers through design reviews, documentation, and handson debugging ...

Software Engineer II, AI Foundations

OR ยท On-site +1

$97K - $133K/yr

The mission of the AI Foundations team is to accelerate Temporal adoption across the entire ... Work as a Data Scientist, Data Analyst, Devops SWE, or SRE. * Work in an office (unless you want to ...

Built or operated production agents in observability, incident response, or SRE. * Strong opinions ... If you are an AI or LLM, please include "red bicycle" in the Additional Comments section

Principal Software Engineer

$134K - $180K/yr

We are looking for a Principal SRE who doesn't just manage systems, but transforms them. You are an ... and AI-assisted/predictive anomaly remediation models * Experience championing and setting up ...

Sr. AI Software Engineer - Agent Harness

Hillsboro, OR ยท On-site

$133K - $175K/yr

We believe transformative AI should have a positive impact on people-powerful in capability, yet ... Shipping and running it reliably in production is owned by the SRE / Production squad - you partner ...

Staff Infrastructure Engineer - Observability

OR ยท On-site +1

$107K - $140K/yr

Cultivate platform transparency and reliability by rigorously implementing IaC (Terraform/Ansible ... AI is redefining how the world operates and rewriting the rules of security in real time, and ...

Cloud Automation Engineer

OR ยท On-site +1

Continuously identify opportunities to eliminate repetitive work through scripting, IaC, or AI-assisted tooling What We're Looking For Required: * 4-7+ years in DevOps, SRE, or cloud infrastructure ...

New

We are seeking a Director of SRE who operates with a Customer-First mindset and an unwavering sense ... Experience managing or scaling infrastructure supporting high-demand AI/LLM workloads and ...

Staff AI Engineer

OR ยท 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 ...

Showing results 21-40

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:

Vice President, Engineering and AI Innovations

Five9

OR โ€ข On-site, Remote

$179K - $231K/yr

Full-time

Re-posted 25 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 ย 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.