1

Ai Reliability Engineer Jobs (NOW HIRING)

Site Reliability Engineer

Frederick, MD · Hybrid

$56.75 - $75.25/hr

Integrate AI-driven tooling into DevOps pipelines for code quality, security scanning, and operational insights * Lead adoption of AI-enhanced SRE practices, including intelligent remediation and ...

Site Reliability Engineer

Frederick, MD · Hybrid

$56.75 - $75.25/hr

Integrate AI-driven tooling into DevOps pipelines for code quality, security scanning, and operational insights * Lead adoption of AI-enhanced SRE practices, including intelligent remediation and ...

SRE Engineer

Redmond, WA · On-site

$63.75 - $84.75/hr

Deploy and manage AI resources on Microsoft Azure, including AI Foundry and RAG solutions * Monitor and ensure service uptime, availability, reliability, and latency * Track and integrate SRE metrics ...

Site Reliability Engineer - NYC

New York, NY · On-site

$62.25 - $82.75/hr

We democratize AI through high-performance, optimized, open-source and cutting-edge models ... What you will do As a Site Reliability Engineer, you balance the day-to-day operations on ...

Site Reliability Engineer

Washington, DC · On-site

$64.25 - $85.50/hr

The role focuses on ensuring operational reliability and optimizing system performance for enterprise AI systems. Responsibilities : • Apply core reliability engineering principles to ensure high ...

Reliability Engineer

WV · Remote

$111K - $150K/yr

Skills: DevOps, DevSecOps, Reliability Engineering, Software Engineering, Systems Engineering ... AI-powered career tool that identifies career steps and learning opportunities Support: An internal ...

Site Reliability Engineer (SRE)

Parsippany, NJ · On-site

$57.25 - $76.25/hr

We are looking for a talented Site Reliability Engineer (SRE) with a strong background in Google ... Familiarity with Google BI and AI/ML tools a plus (Looker, BigQuery ML, Vertex AI, etc.) Experience ...

Runpod is the foundational platform for developers to build and run custom AI systems that scale ... The Reliability team owns the availability, performance, and operational excellence of Runpod ...

SRE Architect, AI-Powered Reliability

Chicago, IL · On-site

$58.75 - $78/hr

Define and lead WEX's AI-Powered Reliability Engineering strategy, driving adoption of SRE agents across the software lifecycle-from design and development through deployment and operations, to ...

Define and lead WEX's AI-Powered Reliability Engineering strategy, driving adoption of SRE agents across the software lifecycle-from design and development through deployment and operations, to ...

Define and lead WEX's AI-Powered Reliability Engineering strategy, driving adoption of SRE agents across the software lifecycle-from design and development through deployment and operations, to ...

SRE Architect, AI-Powered Reliability

Portland, ME · On-site

$58.25 - $77.50/hr

Define and lead WEX's AI-Powered Reliability Engineering strategy, driving adoption of SRE agents across the software lifecycle-from design and development through deployment and operations, to ...

next page

Showing results 1-20

Ai Reliability Engineer information

See salary details

$61K

$118K

$141K

How much do ai reliability engineer jobs pay per year?

As of Jun 19, 2026, the average yearly pay for ai reliability engineer in the United States is $117,973.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,500.00 and $129,000.00 per year, depending on experience, location, and employer.

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 are AI Reliability Engineers?

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.
More about Ai Reliability Engineer jobs
What cities are hiring for Ai Reliability Engineer jobs? Cities with the most Ai Reliability Engineer job openings:
What states have the most Ai Reliability Engineer jobs? States with the most job openings for Ai Reliability Engineer jobs include:
What job categories do people searching Ai Reliability Engineer jobs look for? The top searched job categories for Ai Reliability Engineer jobs are:
Infographic showing various Ai Reliability Engineer job openings in the United States as of June 2026, with employment types broken down into 75% Full Time, and 25% Contract. Highlights an 87% In-person, and 13% Remote job distribution, with an average salary of $117,973 per year, or $56.7 per hour.

Principal Site Reliability Engineer (SRE)

INFINITE CHOICE LLC

San Francisco, CA • Remote

$180K - $210K/yr

Full-time

Posted 24 days ago


Job description

About the Role

We're seeking an exceptional Principal Site Reliability Engineer to architect, design, and build our SRE foundation from the ground up at InfiniteChoice. This is a rare greenfield opportunity to establish SRE practices, develop custom tooling, and create the reliability culture that will support our platform serving millions of users and billions in transaction volume.

As our Principal SRE, you'll combine deep technical expertise with strategic vision to build world-class monitoring, observability, and automation systems. You'll have the autonomy to define our SRE processes, select technologies, and create the framework that ensures our systems are reliable, scalable, and performant.

Location: Remote - US based

What You Will DoSRE Foundation & Process Development
  • Build SRE practices from scratch - define SLIs, SLOs, error budgets, and reliability metrics

  • Establish incident response procedures, on-call rotations, and post-mortem processes

  • Create reliability engineering standards and best practices across all engineering teams

  • Develop disaster recovery and business continuity strategies

  • Design and implement capacity planning and performance optimization frameworks

Architecture & Tool Development
  • Drive architecture decisions for comprehensive application and infrastructure monitoring solutions

  • Design and develop custom SRE tools for automated monitoring, alerting, and remediation

  • Build observability platforms that provide deep insights into system performance and user experience

  • Create automation frameworks for deployment, scaling, and incident response

  • Architect logging, metrics, and tracing systems for distributed microservices environments

Google Cloud Infrastructure Excellence
  • Leverage Google Cloud Platform services to build resilient, scalable infrastructure

  • Implement cloud-native monitoring using Stackdriver, Cloud Monitoring, and Cloud Logging

  • Design auto-scaling and self-healing systems using GKE, Cloud Functions, and managed services

  • Optimize cloud costs while maintaining high availability and performance standards

  • Establish security and compliance frameworks within GCP environments

Innovation & Continuous Improvement
  • Research and implement cutting-edge SRE tools and methodologies

  • Leverage AI and machine learning for predictive analytics, anomaly detection, and automated remediation

  • Create dashboards and reporting systems that provide actionable insights to engineering and business teams

  • Establish feedback loops for continuous improvement of reliability and performance

  • Stay current with industry best practices and emerging technologies in the SRE space

What You Must HaveSRE & Infrastructure Expertise
  • 12+ years of experience in Site Reliability Engineering or Infrastructure Engineering

  • 5+ years in lead SRE roles building and scaling SRE teams and processes

  • Proven track record designing and implementing monitoring and observability solutions at scale

  • Deep understanding of distributed systems, microservices architectures, and cloud-native patterns

  • Experience with infrastructure as code, configuration management, and deployment automation

Google Cloud Platform Proficiency
  • Hands-on experience with Google Cloud Platform is required

  • Expertise with GCP monitoring and observability stack (Cloud Monitoring, Cloud Logging, Cloud Trace)

  • Experience with GKE, Compute Engine, Cloud Functions, and other core GCP services

  • Knowledge of GCP networking, security, and compliance capabilities

  • Understanding of GCP cost optimization and resource management

Technical Skills
  • Strong programming skills in Python, Go, Java, or similar languages

  • Experience with monitoring tools (Prometheus, Grafana, Datadog, New Relic, or similar)

  • Proficiency with containerization (Docker, Kubernetes) and orchestration platforms

  • Knowledge of CI/CD pipelines, automated testing, and deployment strategies

  • Understanding of database performance tuning and optimization (SQL and NoSQL)

AI & Automation
  • Familiarity with AI-driven development tools and methodologies is a huge plus

  • Experience with machine learning for operations (AIOps), anomaly detection, or predictive analytics

  • Knowledge of automated incident response and self-healing systems

  • Understanding of AI/ML tools for log analysis, pattern recognition, and intelligent alerting

Problem-Solving & Mindset
  • Strong analytical and troubleshooting skills for complex distributed systems

  • Experience with high-pressure incident response and crisis management

  • Detail-oriented with commitment to operational excellence and continuous improvement

  • Comfortable with ambiguity and building processes in a fast-growing environment

  • Passion for reliability, automation, and engineering best practices

  • Demonstrated experience building SRE programs and processes from the ground up is a HUGE plus

Education
  • Bachelor's degree in Computer Science, Engineering, or equivalent professional experience

  • Industry certifications (Google Cloud Professional, SRE or related certifications preferred)

What We Offer
  • Ground-floor opportunity to build SRE practices and culture from scratch

  • Full autonomy to define processes, select technologies, and establish best practices

  • Direct impact on platform reliability serving millions of users

  • Opportunity to create lasting engineering culture and operational excellence

  • Remote-first culture with in-person meeting in Dallas, TX on need basis

  • Collaborative environment with smart, passionate engineers and cross-functional teams

  • Access to cutting-edge technologies and AI-driven development tools

  • Competitive compensation, equity participation, and comprehensive benefits

Ready to Build World-Class Reliability?

Join us in creating the SRE foundation that will power InfiniteChoice's next phase of growth. If you're passionate about reliability engineering, love building systems from scratch, and want to establish the operational excellence that scales with our business, we'd love to hear from you.

About InfiniteChoice

InfiniteChoice was founded to help people find the experiences they want simply and effortlessly. We leverage a new type of business model and platform that uniquely applies automation and technology to solve the challenges of scale and complexity in experience discovery.


Existing business and marketing technologies can no longer handle the demands of connecting millions of consumers with vast inventories of experiences across a fragmented, global marketplace of people, partners, and providers.


Our mission is to disrupt this status quo by creating seamless connections between consumers and experiences. We're just at the beginning of this journey, but our approach is working: we've helped over 275 million visitors connect to millions of experiences, generating over $2 billion in revenue for our brands and partners.