Technical Lead - AI OPs

TIAA•Frisco, TX

3d•$130,000 - $154,000•Onsite

About The Position

We are seeking a highly skilled and visionary Technical Lead, AIOps, to join our growing AI Operations team. In this pivotal role, you will drive the transformation of IT operations through the strategic application of Artificial Intelligence, Machine Learning, and Big Data analytics. You will architect and deliver cutting-edge automated solutions that leverage observability platforms, advanced ML algorithms, and robust data analysis frameworks to improve system resilience, production availability, and operational efficiency. This is a technical leadership position at the intersection of innovation and operations. You will lead a team of high-performing Site Reliability and AIOps engineers, guiding them through complex technical challenges while fostering a culture of collaboration, continuous improvement, and innovation.

Requirements

Bachelor's Degree Required
5 Years Required; 7 Years Preferred
Sedentary Work
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

Nice To Haves

At least 7+ years of experience in a technology role.
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
Demonstrated ability to lead and develop high-performing engineering teams
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

Responsibilities

Design and implement a robust, enterprise-grade AIOps platform supporting production operations teams across the full incident lifecycle — from initial observation through engagement and resolution.
Integrate observability platforms such as Dynatrace, Moogsoft, and Splunk with AI/ML capabilities to enable early anomaly detection, trend analysis, and actionable operational insights.
Build and maintain an agentic AI-powered virtual assistant that delivers instant, intelligent responses to operational queries — including incident summaries, root-cause analysis, and recommended remediation steps.
Design and maintain interactive dashboards providing real-time visibility into key operational metrics such as MTTA and MTTR, enabling proactive decision-making across engineering and leadership teams.
Collaborate with the GAIT Center of Excellence to implement GenAI-based solutions that automate report generation and streamline operational workflows.
Partner with Lines of Business development teams to automate routine tasks and reduce manual intervention.
Architect and implement AI/ML algorithms tailored to boost IT operational efficiency, predict system failures, and recommend preventive actions before issues impact end users.
Lead, mentor, and develop a team of Site Reliability and AIOps engineers.
Engage effectively with both technical and non-technical stakeholders to ensure AIOps tools are understood, valued, and widely adopted across the organization.