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 an AI software engineer - design, build, deploy and maintain AI, ML and GenAI powered software solutions. Work on bridging software engineering and machine learning by transforming models into scalable, secure, and production-ready systems that solve real business problems. Experience in handling LLMs, prompt engineering, embeddings, and vector databases. Delivery using leading-edge and/or proven technologies, working closely with stakeholders to meet requirements and expectations. Working in an Agile, collaborative environment to understand stakeholder requirements, aligning with team goals and objectives.
AI & Machine Learning Development
- Design, develop, evaluate, and optimize machine learning and Generative AI solutions
- Select appropriate algorithms and frameworks based on business and technical requirements
- Experience in handling LLMs, prompt engineering, embeddings, and vector databases.
- Hands on experience on handling structured data in generative AI solutions
- Experience on working with RAG solutions
- Experience on working with Front end framework like React.Js
- Hands on experience on Python, REST API, microservices
Software Engineering
- Build scalable, maintainable, and modular AI-driven applications
- Integrate AI models into backend services, APIs, and enterprise systems
- Write clean, testable, and efficient code following best engineering practices
Deployment
- Deploy models or services using containers, cloud platforms
- Monitor solution performance, latency, and reliability in production
Data & Collaboration
- Collaborate with product managers and domain experts
- Work with large structured and unstructured Databases
Security, Ethics & Compliance
- Ensure responsible and ethical AI development
- Address model bias, explainability, privacy, and security concerns
- Comply with organizational and regulatory standards
- Familiarity with Agile development
- Demonstrated ability to operate within short release cycles
- Ability to develop and deploy following best-in-class engineering practices
- Experience designing enterprise level solutions for clients
- Ability to explain complex AI concepts to non-technical stakeholders
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