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Cloud & AI Engineer @ IBM

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IBM  Cloud & AI Engineer

Job Description

  • Design, develop, and enhance backend applications as per business requirements.
  • Maintain and manage applications in a cloud-native environment using Kubernetes/OpenShift.
  • Commit source code using GitHub; perform code reviews to ensure code is up to date, compliant, high quality, and free of vulnerabilities.
  • Work in accordance with Agile methodologies.
  • Share knowledge and contribute to the technical growth and upskilling of team members.
  • Demonstrate excellent communication skills while collaborating with cross-functional teams.
  • Ability to quickly pick up new areas and technologies based on business requirements.

Required education
Bachelor's Degree
Preferred education
Master's Degree

Required technical and professional expertise
  • 3+ years of overall experience in backend application development with a strong understanding of system design and best practices.
  • 3+ years of hands-on development experience in GoLang and/or Python (knowledge of C++ is a plus).
  • Good level of expertise in Kubernetes or OpenShift, including use of Docker/Podman and public cloud providers.
  • Good understanding of Container Networking (CNI) and container-native storage concepts.
  • Strong expertise in version control systems (Git).
  • Experience using cloud technologies such as AWS, GCP, Azure, or IBM Cloud.
  • Hands-on experience with Ansible and Shell scripting.
  • Proficient in Linux system administration.
  • Experience with Infrastructure as Code (IaC) using Terraform.
  • Ability to design and operate a DevOps application lifecycle.
  • Strong understanding of CI/CD pipelines, especially Jenkins, Github Actions, with hands-on experience writing and debugging Jenkinsfiles.
  • Knowledge of Generative AI systems, including:
  • LLM inferencing and model serving, including 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

Preferred technical and professional experience
  • Full-stack development experience using GoLang and/or Python.
  • Advanced expertise in Kubernetes/OpenShift and cloud service providers.
  • Strong knowledge of Generative AI and inferencing, including:
  • Serving LLMs using vLLM in cloud-native environments
  • Scaling and operating inference workloads on Kubernetes/OpenShift
  • Integrating GenAI capabilities into enterprise applications
  • Ability to learn new domains and technologies quickly based on business needs.
  • Excellent written and verbal communication skills.
Years of Experience:
2 - 5

Job Classification

Industry: IT Services & Consulting
Functional Area / Department: Engineering - Software & QA
Role Category: DevOps
Role: Site Reliability Engineer
Employement Type: Full time

Contact Details:

Company: IBM
Location(s): Bengaluru

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Keyskills:   ai engineer kubernetes ibm cloud iac docker ansible cloud deep learning tensorflow git gcp devops jenkins pytorch debugging shell scripting azure python github ai llm upskilling full stack agile aws infrastructure as code

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