Software Engineer - Data & AI Products

At IBM Finance & Operations, we are the backbone of IBM's transformation driving efficiency, transparency, and smart decision-making across the business. Our teams provide the insight and discipline that guide strategy, ensure financial strength, and enable IBM to invest in innovation and growth. Working in Finance & Operations means combining analytical skills with collaboration and curiosity. You'll partner with colleagues across functions and geographies, using data, technology, and process excellence to create solutions that improve performance and deliver measurable impact. IBM offers continuous learning, career development, and a culture that values diverse perspectives. Join us and be part of a global team that keeps IBM moving forward, while building your own future in a dynamic and evolving environment. As a Software Developer: Generalist, you will design, develop, test, and deliver offerings using leading-edge and/or proven technologies. You will work in an Agile, collaborative environment to understand stakeholder requirements and contribute to the development of innovative software solutions. Your primary responsibilities will include: Contribute to evolving existing source data pipelines to an ELT model of data ingestion. Implement the separation of source-aligned data products from aggregate data products. Decorate your data products with metadata to support knowledge transfer, adoption, and the application of Machine Learning and LLMs. Develop and build Data & AI applications and intelligent features, leveraging large language models (LLMs) to enhance data products, under technical guidance. Implement new data pipelines and good to support the training, fine-tuning, and deployment of AI/ML models. Tag and classify your data assets to ensure they are used responsibly throughout the organization, applying masking or restricting access where appropriate. Apply software engineering best practices to your code release process to support CI/CD and a high velocity collaboration model based on InnerSource, including MLOps principles. Register and maintain the catalog entries for your data products and models to support discoverability and reuse. Ensure your data products easily join with other business data products using common identifiers and keys. Develop automated and resilient processes that support the end-end delivery of business value. Required Professional and Technical Expertise Contribute to defining and delivering on a data product SLO for your data ‘customers’. Responsibly share your data products with other internal consumers while balancing the core needs of security and compliance. Contribute feedback and recommendations to the Data Platform team in order to remove friction and increase scale for all users. Write custom adapters to integrate internal data sources into the centralized Warehouse environment. Support and learn from team members on best practices in AI application development and data governance. • Exposure to Back-End Development: Experience working with back-end development technologies, designing, developing, testing, and delivering offerings using leading-edge and/or proven technologies. • Component-Level Solution Development: Exposure to designing, coding, and testing innovative component-level software solutions, ensuring unit testing and readiness for integration into products. • CI/CD Pipeline Contribution: Experience working with automated CI/CD pipelines, contributing to code quality stages, and ensuring seamless integration and delivery. • Debugging and Problem-Solving: Exposure to debugging customer-reported problems, designing, developing, and unit testing code fixes, and collaborating with stakeholders to resolve issues efficiently. • Agile Environment Collaboration: Experience working in an Agile, collaborative environment, understanding stakeholder requirements, and aligning with team goals and objectives. • L3 Support Engineering: Exposure to L3 support engineering practices, including designing, developing, and testing solutions to resolve complex customer-reported problems. • DevOps Engineering: Experience working with DevOps engineering principles, contributing to the automated CI/CD pipeline, and ensuring seamless integration and delivery. • Front-End Development: Exposure to front-end development technologies, designing, developing, testing, and delivering offerings using leading-edge and/or proven technologies. India Infrastructure & Technology Hybrid Professional Bangalore, IN Bangalore (0063) IBM India Private Limited Artificial Intelligence Debugging Engineering Front-end Development Integration Readiness Software Testing Agile Coding Continuous Integration/Continuous Delivery Back-end Development Collaboration Unit Testing Continuous Integration/Continuous Delivery Pipelines Stakeholder Requirements DevOps Engineering