Cloud & AI Engineer

Overview

At IBM Infrastructure & Technology, we are dedicated to designing and managing the systems that sustain global operations. Our portfolio ranges from highly resilient mainframes and hybrid cloud solutions to networking, automation, and site reliability. Our teams are committed to delivering the performance, security, and scalability that clients and industries rely on daily. A career in Infrastructure & Technology involves addressing intricate challenges through curiosity and teamwork. You will collaborate with a diverse array of technologies and colleagues from around the globe to create resilient, future-focused solutions that drive innovation. IBM fosters continuous learning, career development, and a supportive culture, providing you with the opportunity to enhance your expertise and influence the infrastructure that propels progress.

Responsibilities

• Architect, develop, and improve backend applications according to business needs.
• Oversee and maintain applications in a cloud-native environment utilizing Kubernetes/OpenShift.
• Utilize GitHub for source code management; conduct code reviews to ensure code quality, compliance, and security.
• Adhere to Agile methodologies in all tasks.
• Promote knowledge sharing and contribute to the technical development and skill enhancement of team members.
• Exhibit strong communication skills while working collaboratively with cross-functional teams.
• Demonstrate the ability to rapidly learn new technologies and areas based on business demands.
  
  

Preferred Educational Background

Master's Degree

Essential Technical and Professional Qualifications

• A minimum of 4 years of experience in backend application development, with a solid grasp of system design and best practices.
• At least 4 years of practical development experience in GoLang and/or Python (C++ knowledge is advantageous).
• Proficient in Kubernetes or OpenShift, including experience with Docker/Podman and public cloud platforms.
• Strong understanding of Container Networking Interface (CNI) and container-native storage concepts.
• Expertise in version control systems, particularly Git.
• Familiarity with cloud technologies like AWS, GCP, Azure, or IBM Cloud.
• Hands-on experience with Ansible and Shell scripting.
• Competent in Linux system administration.
• Experience with Infrastructure as Code (IaC) using Terraform.
• Capability to design and manage a DevOps application lifecycle.
• Strong knowledge of CI/CD pipelines, especially with Jenkins and GitHub Actions, along with practical experience in writing and debugging Jenkinsfiles.
• Familiarity with Generative AI systems, which includes:
• LLM inferencing and model serving, particularly experience with vLLM
• Integrating GenAI/LLM inferencing into backend services and APIs
• Experience with deep learning frameworks such as PyTorch, TensorFlow, and Scikit-learn
• Understanding of performance, scalability, GPU utilization, and cost considerations for AI workloads in production
  
  

Desired Technical and Professional Experience

• Experience in full-stack development using GoLang and/or Python.
• Advanced knowledge of Kubernetes/OpenShift and various cloud service providers.
• In-depth understanding of Generative AI and inferencing, including:
• Serving LLMs with vLLM in cloud-native settings
• Scaling and managing inference workloads on Kubernetes/OpenShift
• Integrating GenAI functionalities into enterprise applications
• Ability to swiftly acquire knowledge in new domains and technologies based on organizational requirements.
• Exceptional written and verbal communication abilities.