At CDAO (Chief Data Analytics Office), we drive our firm’s strategic investments in AI/ML and data-oriented tools and capabilities. Our Platform Engineering team is at the forefront of building innovative platforms, automating infrastructure operations, and enabling Agentic-based AIOps platforms. Our mission is to enhance scalability, security, and reliability for CDAO-hosted managed services.

 

As an AIOps Platform Engineer within our platform operations team, you will be tasked with the design, construction, and maintenance of our AIOps solution. This role demands a profound knowledge of AI/ML technologies, IT infrastructure, and platform engineering.

 

Job Responsibilities:

Design and implement a robust AIOps platform to support the AI/ML and Data organization's operational needsCollaborate with data scientists, machine learning engineers, and platform operations teams to integrate AI/ML agents into the platformDevelop and maintain data pipelines and workflows to ensure efficient data collection, processing, and analysis to provide actionable intelligence for agents.Implement monitoring and alerting systems to ensure the platform's reliability, availability, and performanceAutomate routine tasks and processes to enhance operational efficiency and reduce manual interventionTroubleshoot and resolve platform-related issues, ensuring minimal impact on AI/ML operationsStay current with industry trends and advancements in AIOps, AI/ML, and data engineeringDevelop and deploy agentic systems and agents to automate routine tasks and processes, enhancing operational efficiency

Required qualifications, capabilities and skills:

Bachelor’s degree in Computer Science, Mathematics, or a related fieldProven experience in platform engineering, with a focus on AI/ML technologies and data operationsStrong programming skills in languages such as Python, Java, or ScalaExperience with cloud platforms (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes)Familiarity with data processing frameworks (e.g., Apache Kafka, Apache Spark) and IT monitoring tools (e.g., Prometheus, Grafana, Datadog)Knowledge of machine learning algorithms and data analysis techniques.Experience working with agentic systems and agents for automationExcellent problem-solving skills and the ability to work collaboratively in a fast-paced environmentStrong communication and interpersonal skills

Preferred qualifications, capabilities and skills:

Master's degree in a related fieldCertifications in cloud computing, AI/ML, or data engineering (e.g., AWS Certified Machine Learning, Google Professional Data Engineer)Experience with DevOps practices and CI/CD pipelines