Sr Cloud Platform & Site Reliability Engineering Lead

National Life Insurance•Addison, TX

10d•Onsite

About The Position

The Senior Cloud Platform & Site Reliability Engineering Lead partners with business and technical stakeholders to lead cloud platform design, engineering, and integration efforts. This individual has a proven track record of driving continuous improvement across infrastructure, platform services, and application reliability. This role is a senior technical leadership position within the National Life Group IT Shared Services team. You will represent cloud and platform engineering in project initiatives, architecture design, and operational excellence while collaborating across a vibrant technical community. We’re looking for an inquisitive individual with a passion for continuous learning, attention to detail, and a drive to follow-through.

Requirements

Bachelor’s degree, preferred in Computer Science; or relevant work experience.
8+ years of hands-on with CI/CD pipelines, APM tools, source code management, infrastructure, cloud, or platform engineering experience with at least 4 years in a technical leadership role.
Open-minded with proven ability to work collaboratively with others.
Show up consistently with a positive attitude.
Demonstrated ability to lead in a highly matrixed, heavily outsourced organization through influence and partnership.
Ability and interest in mentoring technical staff and raising collective technical competencies.
Ability to manage change and operate effectively in complex environments.
Broad engineering awareness with strong expertise in multiple of the following areas – Microsoft Azure (compute, storage, networking, identity, monitoring)
Infrastructure as Code (Bicep, ARM, Other)
Pipeline Technologies (Azure DevOps, GitHub Actions, CI/CD)
Code Repository Management (GIT)
Monitoring & Instrumentation Tools (Azure Monitor, Application Insights, New Relic or similar)
Containers & Serverless (AKS, Azure Functions)
Proficiency in scripting and automation (Python, PowerShell, etc.)
DevSecOps tools (SonarQube, JFrog, SwaggerHub or similar)

Nice To Haves

Experience with AWS or other cloud platforms is a plus
Exposure to AI technologies in development and application performance (AIOps)

Responsibilities

Lead design and delivery of cloud-native solutions within Microsoft Azure and other.
Lead development and enhancement of CI/CD, SRE, and observability capabilities.
Drive infrastructure automation using Infrastructure as Code (Bicep, ARM, other).
Serve as a subject matter expert in pipeline configuration, code repository management, and related controls.
Help lead incident resolution and business issue remediation.
Lead identifying and managing capacity, performance, and risk.
Adhere to and promote firm Change Management and Problem Management policies (ITIL).
Possess the ability to communicate effectively with appropriate detail across all levels.
Lead adoption of SRE practices including SLIs/SLOs and reliability engineering principles.
Drive improvements in system reliability, scalability, and performance.
Leverage Azure Monitor, Application Insights, and APM tools such as New Relic for observability.
Promote automation and AI-assisted operations to reduce manual effort and improve outcomes.
Drive innovation and remain current on Azure and emerging cloud technologies.
Define and promote Azure architecture standards (networking, identity, security).
Lead adoption of cloud-native patterns (AKS, serverless, PaaS services).
Collaborate with development, QA, and operations teams to integrate CI/CD and observability practices.
Communicate effectively with stakeholders across engineering and business teams.
Leverage approved AI tools, where appropriate, to improve the efficiency, quality, and impact of their work.
Stay curious and open to new AI-enabled ways of working.
Exercise sound judgment by reviewing and validating AI-generated content.
Maintain accountability for the accuracy, quality, fairness, and integrity of work products by adhering to National Life’s AI guiding principles.
Use AI responsibly and in accordance with company policies related to confidentiality, data privacy, security, compliance, retention and intellectual property.