Rise to meet the challenge of solutioning the world's problems. Software engineers at IBM get to see their work in the real world, improving the current state of disaster preparedness and providing more accurate medical solutions around the globe. You will be challenged to think outside the box, work across organizations, and engineer creative solutions that scale to the demands of our ever-growing customer base. Take ownership and be actively engaged in the entire product lifecycle, from quick hits to full feature development.
- Lead and participate in software design and code reviews, to ensure a high level of software quality delivered to customer
- Drive the delivery of high impact projects for delivery into enterprise production environments.
- Lead and adhere to professional software engineering practices using such most common tools and practices in software enterprise business (e.g. Test Driven Development, Continuous Integration tools, Source Code Management, etc.)
- Participate in and lead the planning, creation and execution of automated test stack for developed features
- Maintain a high level of proficiency within the area of overall Software Engineering knowledge and contribute to the technical skills growth of other team members
- Participate in customer engagements (enhancement requests, issue resolution, etc.)
- Work well independently and as part of a bigger team
• Proficiency in cloud platforms such as IBM Cloud, AWS, Azure, or Google Cloud.
• Strong knowledge of programming and scripting languages (e.g., JavaScript/TypeScript, Java). Creating prototypes and PoCs for full stack solutions
• Ability to design and implement cloud infrastructure, including auto-scaling, serverless computing, and distributed databases.
• Understanding of cloud security principles and best practices, including identity and access management (IAM), data encryption, and compliance with security frameworks (e.g., ISO 27001, NIST, FIPS, HIPAA).
• Experience with Kubernetes or OpenShift for container orchestration, including deployment, scaling, and management of containerized applications.
• (optional) Experience in developing and deploying AI and machine learning models, including familiarity with frameworks like TensorFlow, PyTorch, or scikit-learn.
• (optional) Knowledge and experience with large language models, including fine-tuning and deploying models for various applications.
• (optional) Proven ability to design and optimize AI workflows