AI-Ops Engineer

AI-Ops Engineer 1464463

• Hourly pay: $60/hr
• Worksite: Leading university (Stanford, CA 94305 - Hybrid, Must be onsite 2–3 days on campus)
• W2 Employment, Group Medical, Dental, Vision, Life, Retirement Savings Program, PSL
• 40 hours/week, 12 Month Assignment, Possible extension or conversion

A leading university seeks an AI-Ops Engineer. The successful candidate will be responsible for evolving traditional DevOps into AI- Ops at the Engineering Center. This role leverages AI and machine learning to automate and enhance IT operations. The company offers a family-oriented culture and environment!

AI-Ops Engineer Responsibilities:

• AI-Driven Operations & Automation
  • Implement AIOps solutions that use ML algorithms to automate performance monitoring, workload scheduling, and infrastructure management.
  • Build anomaly detection systems that identify infrastructure issues before they impact users.
  • Create predictive maintenance workflows that analyze historical patterns to proactively mitigate issues.
• Observability & Intelligent Monitoring:
  • Architect comprehensive observability platforms that aggregate data from disparate sources into unified dashboards.
  • Implement intelligent alerting systems using NLP and ML to reduce alert fatigue and surface actionable insights.
  • Deploy application performance monitoring (APM) solutions integrated with AI-driven analytics. Ensure end-to-end visibility across cloud infrastructure, applications, and AI/ML workloads.
• Cloud Infrastructure & DevOps:
  • Design, build, and maintain scalable, secure AWS infrastructure using Infrastructure as Code (CloudFormation, Terraform, or CDK).
  • Implement and manage containerized environments using Docker, AWS ECS, Fargate, and Kubernetes (EKS).
  • Build CI/CD pipelines for continuous delivery, integrating AI-powered code quality and deployment optimization.
• Collaboration & Continuous Improvement:
• Partner with cross-functional teams to implement domain-agnostic AIOps solutions across the organization.
• Use Git-based version control and code review best practices as part of a collaborative, agile workflow.
• Document operational procedures, runbooks, and AIOps workflows for team knowledge sharing.
• Occasional on-call responsibilities for critical infrastructure.

AI-Ops Engineer Qualifications:

• 3+ years of experience in DevOps, SRE, or Cloud Engineering roles.
• 2+ years of hands-on experience with AWS infrastructure (EC2, ECS, Lambda, S3, IAM, VPC).
• Experience implementing monitoring, observability, and alerting solutions at scale.
• Bachelor's degree in Computer Science, DevOps, Cloud Engineering, or a related field (Master's preferred).
• AWS certification preferred (Solutions Architect, SysOps Administrator, or DevOps Engineer); Professional-level certification a plus.
• Familiarity with ML/AI concepts and their application to operational automation.
• Languages: Python (required); Bash, Go, or TypeScript preferred.
• AIOps & Monitoring: CloudWatch, X-Ray, Prometheus, Grafana, Datadog, or Splunk with ML capabilities.
• Infrastructure as Code: AWS CloudFormation, Terraform, or AWS CDK.
• Containers & Orchestration: Docker, AWS ECS/Fargate, Kubernetes (EKS).
• AWS Services: Lambda, EC2, S3, API Gateway, EventBridge, CloudWatch, IAM, VPC, CodePipeline, SageMaker.
• CI/CD Tools: GitHub Actions, AWS CodePipeline, Jenkins, or GitLab CI.
• Data & Analytics: Experience with log aggregation, metrics analysis, and event correlation platforms.
• Strong understanding of AIOps principles—using AI to enhance, not just support, IT operations is preferred.
• Passion for automation and eliminating manual, repetitive operational tasks is preferred.
• Excellent problem-solving, debugging, and root cause analysis skills are preferred.
• Demonstrated ability to learn rapidly, adapt to new technologies, and continuously improve is preferred.
• Strong communication skills withthe ability to collaborate across technical and non-technical teams are preferred.
• Commitment to reliability, security, and operational excellence is preferred.
• Thrives in a fast-paced, evolving environment, proactively seeking opportunities to embed intelligence into systems and processes is preferred.
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Shift:

• Monday to Friday 9 am - 6 pm.

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