Cloud & AI Engineer at IBM

📋 Job Details at a Glance 📍 Location Bangalore, IN 🏢 Company IBM 👥 Experience 0-2 years 🎓 Qualification Relevant technical qualification and demonstrated shipping experience 📅 Eligible Batch 2023, 2024, 2025, 2026 📄 Job Type Full Time 💰 Salary Not Disclosed 🏢 Industry Technology 🛠 Key Skills Cloud Infrastructure Design Hybrid Cloud Platforms Site Reliability Engineering Networking Automation Mainframe Systems Management Cloud & AI Engineer at IBM — Full Details & How to Apply IBM is hiring a Cloud & AI Engineer in Bangalore, IN , offering a unique opportunity to work on cutting-edge hybrid cloud platforms and AI-driven infrastructure. This role is part of IBM ’s ongoing expansion in Bangalore, IN jobs , with a focus on scalable solutions for global enterprises. The demand for Cloud & AI Engineer jobs is growing rapidly as companies seek to modernize their IT infrastructure and leverage AI for operational efficiency. IBM , a leader in the Technology industry, is at the forefront of this shift, with its hybrid cloud platforms and AI initiatives driving innovation across sectors. This role is a key part of IBM’s strategy to deliver next-generation solutions that meet evolving business needs. IBM stands out as an employer due to its global scale, commitment to innovation, and robust career development programs. The company is expanding its Bangalore, IN jobs portfolio, with a focus on hiring skilled engineers who can contribute to large-scale cloud and AI projects. IBM’s recent investments in hybrid cloud and AI technologies make this an ideal environment for professionals looking to grow in the Technology industry. 2023, 2024, 2025, 2026 graduates with Relevant technical qualification and demonstrated shipping experience and 0-2 years experience are eligible to apply. The salary for this role is Not Disclosed , but the opportunity includes exposure to advanced technologies and a competitive work environment. This role will allow you to work with Cloud Infrastructure Design , Hybrid Cloud Platforms , Site Reliability Engineering , Networking Automation , and Mainframe Systems Management

• These skills are critical for building scalable and secure systems, opening doors to advanced roles in cloud architecture and AI development. The experience gained here can lead to leadership positions in enterprise IT and AI innovation. 📊 Role Difficulty: Medium Competition Level: Medium Fresher Friendly: Yes NexisGrow.com features this opportunity as part of its curated tech job listings. All details are sourced from the official job posting. Apply online before the opportunity closes. Job Role & Responsibilities The Cloud & AI Engineer at IBM is tasked with designing and implementing innovative solutions that leverage cloud infrastructure and AI technologies to enhance operational efficiency. Design and implement cloud infrastructure solutions using tools like AWS and Azure to support scalable applications. Develop and maintain hybrid cloud platforms that integrate on-premises and cloud resources for optimal performance. Utilize site reliability engineering practices to ensure high availability and reliability of cloud services. Automate networking tasks using Ansible and Terraform to streamline deployment processes. Manage mainframe systems to ensure seamless integration with cloud environments and enhance data accessibility. Monitor and analyze system performance metrics to identify areas for improvement in cloud operations
• Collaborate with cross-functional teams to gather requirements and deliver tailored AI solutions that meet business needs. Document processes and solutions to facilitate knowledge sharing and support continuous improvement initiatives. This role fosters an ownership culture, allowing you to directly impact the success of IBM by delivering cutting-edge solutions that drive innovation. Required Skills & Technical Competencies The ideal candidate will possess a robust technical skill set that aligns with the demands of the Cloud & AI Engineer position at IBM
• Technical Skills Cloud Infrastructure Design — entry — Applied to create scalable and efficient cloud environments using AWS and Azure
• Hybrid Cloud Platforms — entry — Used to integrate on-premises and cloud resources for enhanced operational flexibility. Site Reliability Engineering — entry — Implemented to ensure the reliability and performance of cloud services. Networking Automation — entry — Employed tools like Ansible and Terraform to …