IBM Hiring Cloud and AI Engineer Job | Best Opportunity
A Cloud and AI Engineer designs, deploys, and manages cloud-based infrastructure, ensuring optimal performance and scalability. They develop and integrate AI solutions, leveraging machine learning algorithms and big data analytics to enhance business operations and decision-making processes. Proficiency in cloud platforms, AI tools, and coding is essential for this role.
- Job Role: Cloud and AI Engineer
- Salary: Not Disclose
- Location: Bengaluru
- Job Type: Full-Time
- Company: IBM
About Company:
IBM, founded in 1911, is a worldwide chief in era and consulting, renowned for its improvements in AI, cloud computing, quantum computing, and blockchain. With a commitment to diversity and inclusion, IBM fosters a surrounding of non-stop getting-to-know and collaboration. The company helps many Fortune 50 companies, riding advancements in numerous industries via its cutting-edge answers. IBM is dedicated to leveraging technology to enhance commercial enterprise, society, and human circumstances, usually reinventing itself to fulfill contemporary demanding situations.
Role Overview:
As a Cloud and AI Engineer at IBM, you may lay and broaden both the front-stop and back-quit applications, dealing with them in Cloud Native environments with the use of Kubernetes or OpenShift. You’ll devote supply code through GitHub, perform code opinions, and paintings inside Agile frameworks. Proficiency in GoLang, Python, or Java, and enjoy with Docker, Ansible, Terraform, and deep gaining knowledge of frameworks like PyTorch and TensorFlow are vital. You’ll collaborate with go-functional teams, mentor peers, and live up to date with cutting-edge technologies. This function needs strong problem-solving skills, adaptability, and extraordinary verbal exchange to force innovation and hold high standards of security and high quality.
Role and Responsibilities of an IBM Cloud and AI Engineer Job:
Full Stack Development: Design, increase, and beautify each of the front-stop and lower back-end programs to meet business requirements.
Cloud Native Environment Management: Maintain and manage programs in Cloud Native surroundings with the usage of Kubernetes/OpenShift.
Version Control and Code Reviews: Commit supply code via GitHub, carry out code evaluations, and ensure code is up-to-date, compliant, and freed from vulnerabilities.
Agile Methodologies: Work with Agile methodologies, contributing to sprints and participating in each day’s stand-ups, sprint planning, and retrospectives.
Team Collaboration: Share information and make contributions to the technical abilities increase of team members, fostering a collaborative environment.
Communication and Leadership: Demonstrate terrific verbal exchange and leadership competencies, facilitating effective teamwork and assignment execution.
Learning and Adaptability: Show the potential to quickly learn new areas primarily based on evolving commercial enterprise requirements and integrate them into the improvement method.
Required Technical and Professional Skills:
Full Stack Development Experience: At least 6 years of experience in full stack improvement with a sturdy understanding of device design and exceptional practices.
Programming Languages: Proficient in GoLang, Python, and Java; understanding of C++ is a plus.
Container Orchestration: Expertise in Kubernetes or OpenShift, which includes the usage of Docker/Podman for containerization.
Cloud Technologies: Experience with cloud carrier providers together with AWS, GCP, Azure, or IBM Cloud.
Version Control Systems: Proficient in Git for version manipulation.
Automation and Scripting: Experience with Ansible and Shell scripting.
Linux Administration: Proficient in Linux administration duties.
Infrastructure as Code (IaC): Experience with Terraform for IaC.
DevOps Practices:
Design and preserve purposeful DevOps application lifecycles with a terrific knowledge of CICD pipelines, especially the usage of Jenkins; hands-on enjoyment with writing and debugging Jenkins files.
Build Tools: Experience with building equipment inclusive of Maven, Gradle, Make, and Ant.
AI and Deep Learning Frameworks:
Knowledge of deep getting-to-know frameworks such as Pytorch, TensorFlow, Scikit, and Generative AI, with the capacity to combine AI functionalities into applications.
Preferred Technical and Professional Skills:
Advanced Full Stack Development: Advanced expertise in complete stack development with GoLang, Python, and Java.
Container Orchestration Expertise: Deep knowledge of Kubernetes/OpenShift and cloud provider companies.
AI Integration: Advanced expertise of deep gaining knowledge of frameworks and Generative AI, with demonstrated potential to integrate AI into packages.
Adaptability: Demonstrated capability to fast study and adapt to new enterprise regions and technologies as required.
Communication: Strong communique abilities, permitting effective collaboration and knowledge sharing in the group.
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