AI Operations Engineering Technical Leader

Builds Operations (AI Ops) Solutions for specific domains. Automates and optimizes IT operations processes, managing risk, incident management, and root cause analysis using artificial intelligence (AI) and machine learning (ML) techniques. AI Ops aim to reduce the time and effort needed for IT processes while increasing the precision and speed of problem-solving through optimizing the end-to-end lifecycle of artificial intelligence (AI) applications and systems. Collaborates with cross-functional teams, including data scientists, SWEs, and infrastructure/operations, to ensure the reliability, scalability, and performance of IT applications. Automates routine tasks and implements continuous integration/continuous deployment (CI/CD) pipelines to optimize AI Ops processes and workflows. What You’ll Do. Designs and architects end-to-end AI Ops solutions tailored to functional needs, considering factors like scalability, security, and compliance. Establishes proactive monitoring practices, leveraging AI-driven anomaly detection and predictive analytics to anticipate and prevent incidents before they occur. Oversees the deployment and configuration of monitoring and alerting solutions that track the performance of applications, infrastructure, and services. Develops automation frameworks and toolsets to enable self-service AI Ops capabilities for development teams. Translates machine learning concepts into AI Ops solutions by leveraging AI Ops platforms and tools to inform data understanding and operational insights. Shapes a unified platform for AI Ops consisting of microservices and applications that leverage data and ML/AI to build and deliver differentiated full-stack observability and analytics solutions. Fosters collaboration between cross-functional teams including IT operations, development teams, data science, product development, and other stakeholders to identify opportunities for AI-driven improvements. Minimum Qualifications. Bachelors + 8 years of related experience, or Masters + 6 years of related experience, or PhD + 3 years of related experience. Preferred Qualifications. Varies based on the team and business needs | Preferred Qualifications are desired education, experience, and skills that are in addition to Minimum Qualifications.