AI DevOps Tech Lead

Introduction

At IBM Infrastructure & Technology, we design and operate the systems that keep the world running. From high-resiliency mainframes and hybrid cloud platforms to networking, automation, and site reliability. Our teams ensure the performance, security, and scalability that clients and industries depend on every day. Working in Infrastructure & Technology means tackling complex challenges with curiosity and collaboration. You'll work with diverse technologies and colleagues worldwide to deliver resilient, future-ready solutions that power innovation. With continuous learning, career growth, and a supportive culture, IBM provides the opportunities to build expertise and shape the infrastructure that drives progress.

Your role and responsibilities

As a Senior DevOps Platform Engineer, you will be responsible for designing, building, and maintaining astandardized, reusableDevops platform that enables consistent, secure, and efficient delivery of multiple components and teams within a cornerstone initiative of IBM's AI infrastructure portfolio.

This role focuses onenterprise-scale DevOps platform engineering, providingsecure, reliable, and highly automated delivery pipelines. You will act as atechnical leader, driving DevOps strategy, defining standards, modernizing delivery pipelines using the latest tools and practices, and mentoring engineers to improve overall DevOps maturity.

The CI/CD platform you build will enable the faster and secure development and delivery of multiple components by providing a standardized, scalable, and reusable CI/CD framework shared across teams as well as different architectures.

Required education
Bachelor's Degree

Preferred education
Bachelor's Degree

Required technical and professional expertise

• Design, build, and own ashared architecture-agnostic CI/CD platformacross teams.
• Implement and enhanceend-to-end robust delivery pipelinesfrom development and test through staging and production.
• Design and implementautomated testing frameworksfor across various test buckets including Component level tests, unit tests, Operation and model-level tests.
• Collaborate with different component owners and identify the needs in the respective build & test phases and implement it in this common DevOps pipeline.
• Establish and maintainstandardized pipeline templatesfor build, test, security scanning, packaging, and deployment to align with IBM standards and enforcequality gates, compliance checks, and security controlsacross all pipelines.
• Implement controlled deployment strategies such asblue-green, canary, and A/B deploymentswhere applicable.
• Continuouslyoptimize pipeline performance, reliability, and execution timeby adoptinglatest DevOps tools, technologies, and best practices.
• Collaborate with senior technical leadership and establish Roadmap for the project.
• Proactively identify bottlenecks and lead continuous improvement initiatives
• Act astechnical leadfor the CI/CD platform initiative by leading architecture and design discussions with senior stakeholders.
• Providetechnical leadership and mentorship, guiding engineers on DevOps, CI/CD, and testing best practices.

Preferred technical and professional experience

• 12+ years of experience in DevOps, platform engineering, or infrastructure automation.
• Strong expertise in designing and operatingshared, reusable CI/CD platformssupporting multiple teams and components.
• Strong background inautomated testing frameworksand quality engineering
• Hands-on experience withDockerand modern deployment strategies.
• Experience leading teams or acting as atechnical leadin complex environments.
• Excellent problem-solving, communication, and stakeholder collaboration skills.
• Jenkins Mastery with Deep experience in Declarative and Scripted Pipelines, shared libraries, and Jenkins API.
• Proficient in configuring Jenkins with Git (GitHub) and artifact management tools (Artifactory)
• Integrate Jenkins with Docker and Kubernetes for containerized application builds and deployments.
• Strong skills in Python, Bash, and Groovy scripting for pipeline customizations

Nice-to-Have

• Experience with Kubernetes and cloud-native AI platforms.
• Working knowledge ofAI/ML frameworks, including: PyTorch
• Building scalable components for monitoring and benchmarking of LLM-powered features; experience working with LLMs will be advantageous.
• Working knowledge of LLMs and their performance metrics is desirable, particularly in the context of monitoring within DevOps pipelines.
• Experience with managing both dev, test, and production level containers with proper meta-data such as Manifests, tagging, and export control.

Years of Experience:
10-15