Job Description
Who we are
At NTT DATA, we are a global team of over 140,000 professionals, operating in more than 50 countries and serving diverse industries including telecommunications, finance, public sector, healthcare, and more. We are passionate about technology and innovation, and we believe in personalized, merit-based career growth.
We are looking for a highly skilled AI Developer / LLM Engineer to transform complex spreadsheet-based models into scalable, maintainable applications. This role combines deep analytical skills with modern AI and software development expertise, enabling the migration of business-critical logic from Excel into robust application architectures.
What you'll be doing
- Analyse complex Excel and spreadsheet-based models, including workflows, logic, and dependencies
- Understand and document business rules, calculations, edge cases, and implicit assumptions
- Collaborate closely with stakeholders to validate requirements and ensure alignment with business needs
- Define the target application architecture and technical approach for conversion
- Design and develop application-based solutions to replace spreadsheet-driven processes
- Implement AI-assisted or rule-based logic where appropriate
- Write clean, maintainable, and well-documented code
- Ensure full accuracy and parity between existing spreadsheet logic and new application behaviour
- Support testing, validation, and iterative improvements throughout development
What you'll bring along
- BSc/MSc in Computer Science or related field
- Proven experience as an AI Developer or LLM Engineer
- Hands-on experience with Claude (Anthropic) or similar large language models
- Strong programming skills, preferably in Python
- Demonstrated experience analysing and converting complex spreadsheets into applications
- Solid understanding of data processing, calculations, and business logic modelling
- Experience building backend services and APIs
- Ability to work independently, take ownership, and deliver end-to-end solutions
- Experience with cloud platforms ( AWS, Azure, or GCP) is nice to have
- Exposure to Generative AI use cases such as automation, reasoning, or Retrieval-Augmented Generation (RAG)
- Background in data-heavy or analytical domains
