AI-Ops Engineer

AI-Ops Engineer ()

• 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 Dev Ops 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-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 & Dev Ops
  • Design, build, and maintain scalable, secure AWS infrastructure using Infrastructure as Code (Cloud Formation, 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.

• 3+ years of experience in Dev Ops, 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, Dev Ops, Cloud Engineering, or a related field (Master's preferred).
• AWS certification preferred (Solutions Architect, Sys Ops Administrator, or Dev Ops Engineer);
  Professional‑level certification a plus.
• Familiarity with ML/AI concepts and their application to operational automation.
• Languages:
  
  Python (required);
  Bash, Go, or Type Script preferred.
• AIOps & Monitoring:
  Cloud Watch, X‑Ray, Prometheus, Grafana, Datadog, or Splunk with ML capabilities.
• Infrastructure as Code: AWS Cloud Formation, Terraform, or AWS CDK.
• Containers & Orchestration:
  Docker, AWS ECS/Fargate, Kubernetes (EKS).
• AWS Services:
  Lambda, EC2, S3, API Gateway, Event Bridge, Cloud Watch, IAM, VPC, Code Pipeline, Sage Maker.
• CI/CD Tools:
  Git Hub Actions, AWS Code Pipeline, Jenkins, or Git Lab 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 with the 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.

• Monday to Friday 9 am - 6 pm.

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