Design and implement a robust, enterprise-grade AIOps platform supporting production operations teams across the full incident lifecycle
Integrate observability platforms such as Dynatrace, Moogsoft, and Splunk with AI/ML capabilities for anomaly detection and operational insights
Build and maintain an agentic AI-powered virtual assistant for operational queries
Design and maintain interactive dashboards providing real-time visibility into operational metrics
Collaborate with the GAIT Center of Excellence to implement GenAI-based solutions that automate report generation
Architect and implement AI/ML algorithms to boost IT operational efficiency and recommend preventive actions
Lead, mentor, and develop a team of Site Reliability and AIOps engineers

At least 5 years of experience in a Technology Role
Experience with programming languages
Python and/or Java
Experience, hands-on with cloud platforms (AWS, Azure, or Google Cloud)
Experience using observability tools like Moogsoft, Dynatrace, or Splunk
Familiarity with data processing frameworks such as Apache Kafka and automation tools such as Ansible Tower
Solid understanding of machine learning algorithms and data analysis techniques
Practical experience designing and working with agentic systems and automation agents
Excellent problem-solving, communication, and interpersonal skills
Master’s degree in computer science, Data Science, AI/ML, or a related field
Professional certifications in cloud, AI/ML, or data engineering (e.g., AWS Certified Machine Learning Specialty, Google Professional Data Engineer)
Experience with DevOps practices and CI/CD pipelines
Familiarity with Agile development methodologies

Technical Lead – AI Ops

Key skills