Kyndryl is a company that designs, builds, manages, and modernizes mission-critical technology systems. They are seeking a DevOps Technical Leader to architect and scale intelligent automation solutions across enterprise cloud and infrastructure environments, leading the integration of AI-enabled automation into DevOps practices.
Responsibilities:
- Lead the design, implementation, and governance of CI/CD pipelines using GitHub Actions, embedding AI‑driven capabilities to optimize software delivery, deployment quality, and operational workflows
- Architect and oversee intelligent monitoring and observability solutions leveraging Dynatrace, Azure native tools, and AI/ML models to enable predictive insights, anomaly detection, and proactive incident response
- Define and drive infrastructure automation strategies using Terraform, ensuring scalable, secure, and compliant Azure environments aligned with Kyndryl standards
- Serve as a technical mentor and thought leader, guiding DevOps engineers and fostering a culture of continuous improvement, automation, and AI adoption across development and operations teams
- Evaluate and implement emerging Azure and AI technologies, including Azure AI services and Fabric capabilities, aligning automation initiatives with business outcomes and enterprise architecture
- Set the strategic direction for intelligent automation, ensuring solutions are resilient, cost‑effective, and scalable across complex, client‑critical environments
Requirements:
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field
- 7+ years of hands‑on DevOps experience in enterprise or large‑scale environments
- Deep expertise in architecting and optimizing CI/CD pipelines, with demonstrated ability to guide teams in secure and scalable implementations
- Strong proficiency with Dynatrace and Azure monitoring tools
- Advanced experience with Terraform, including defining infrastructure standards and governance across Azure environments
- Proven leadership experience mentoring DevOps engineers and promoting DevSecOps practices
- Strong understanding of enterprise cloud architecture and operational resiliency
- Experience applying AI/ML models for predictive alerting, anomaly detection, or operational optimization
- In‑depth knowledge of Azure AI services (e.g., Azure Machine Learning, Cognitive Services)
- Experience integrating AI into operational workflows, monitoring platforms, or CI/CD pipelines
- Exposure to Azure Fabric or similar AI‑enabled data and analytics platforms
- Experience defining or influencing automation strategy at a program or enterprise level