MCSP Early Professional Hire - Software Developer
This job is no longer available.
Introduction
As a Software Developer Intern with the MultiCloud SaaS Platform (MCSP), you will be involved in multiple areas of the software development project, which is currently staffed and already in place (including back-end and front-end developers, plus SRE engineers). The MCSP will provide you with hands-on experience in developing and testing Cloud-based applications, and any knowledge of development with APIs and/or microservices would be advantageous. Exposure and experience with AWS, IBM Cloud, ROKS, Security and Networking, or Telemetry would stand you out from the rest.
You may be involved in all areas of the Platform, from developing new features and functions to ensuring the production environments remain stable and reliable. We are looking for competent software engineers who already have good programming knowledge, especially with Java, node.js, or Golang
Your role and responsibilities
As a member of this squad, as an MCSP backend developer, you will be part of a dynamic and critical component of our Automation strategy.
- You would be responsible for developing and delivering an automated platform using the latest agile and
- Cloud-native techniques, tools and programming languages.
- You'll work in a dynamic, collaborative environment to understand requirements, design, code and test innovative applications, and support those applications for our highly valued customers.
- You'll employ IBM's Design Thinking to create products that provide a great user experience along with high performance, security, quality, and stability.
- Design and code servers, services, applications and databases that are reusable, scalable and meet critical architecture goals.
- Create Application Programming Interfaces (APIs) that are clean, well-documented, and easy to use.
Required education
None
Preferred education
Bachelor's Degree
Required technical and professional expertise
The following lists technologies we use across MCSP, so knowledge and experience in any of these would be advantageous:
- Background in software engineering with Java, Golang, or node.js,
- Experience automating problems or tasks to improve automation (e.g.,
- Powershell, shell-script, Python, etc.),
- Confident with source control management systems (e.g., GitHub, GitLab),
- General Linux knowledge,
- Happy working using Agile practices, including scrums, sizings,
- retrospectives, and playbacks,
- Experience using CI/CD processes
Preferred technical and professional experience
Bachelor degree in Computer Science, Computer Engineering, Software Engineering, or a related field.
The following lists technologies we use across MCSP, so knowledge and experience in any of these would be advantageous:
- Experience with a logging and analytics framework (e.g., Splunk, LogDNA, or ELK stack),
- Experience with cloud platforms and their services (e.g., IBM Cloud, AWS, GCP, MS Azure),
- Network and security knowledge,
- Experience with Kubernetes and building Operators, ideally with RedHat OpenShift,
- Experience with pipeline tools for deploying and managing applications (Travis, Jenkins).
ABOUT BUSINESS UNIT
IBM Software infuses core business operations with intelligence-from machine learning to generative AI-to help make organizations more responsive, productive, and resilient. IBM Software helps clients put AI into action now to create real value with trust, speed, and confidence across digital labor, IT automation, application modernization, security, and sustainability. Critical to this is the ability to make use of all data, because AI is only as good as the data that fuels it. In most organizations data is spread across multiple clouds, on premises, in private datacenters, and at the edge. IBM's AI and data platform scales and accelerates the impact of AI with trusted data, and provides leading capabilities to train, tune and deploy AI across business. IBM's hybrid cloud platform is one of the most comprehensive and consistent approach to development, security, and operations across hybrid environments-a flexible foundation for leveraging data, wherever it resides, to extend AI deep into a business.
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