About the role

Data Scientist (AI / GenAI)

Job Summary:

SU:CH AI (Shapoorji Pallonji Group) is at the forefront of developing next-generation AI-powered enterprise products across various domains, including Tax Technology and Compliance. We are seeking Data Scientists with specialized expertise in Generative AI and Machine Learning to contribute to impactful AI solutions that transform organizational processes.

Key Responsibilities:

Design, build, and deploy production-grade AI and Machine Learning solutions that drive innovation.
Develop and optimize applications powered by Large Language Models (LLMs) including RAG, GraphRAG, and Agentic AI systems.
Fine-tune and customize LLMs using advanced techniques such as LoRA, PEFT, and transfer learning.
Create intelligent systems for chatbots, recommendations, knowledge retrieval, and enhanced search functionalities.
Design and optimize prompt engineering frameworks tailored for specific business applications.
Develop scalable AI pipelines, model-serving frameworks, and API-based services that ensure operational efficiency.
Collaborate with cross-functional teams to translate complex business problems into AI-driven solutions.
Assess and recommend the latest AI technologies, models, and frameworks for product applicability.
Ensure that deployed models maintain scalability, reliability, security, and are production-ready.

Requirements:

3-6 years of experience as a Data Scientist, AI Engineer, Machine Learning Engineer, or in a similar capacity.
Proven experience in building and deploying production-grade AI applications utilized by end users.
Strong expertise in Generative AI, LLMs, RAG, LangChain, and Python programming.
Solid understanding of model evaluation, performance optimization, and scalability best practices.
Experience integrating AI solutions within enterprise applications and demonstrating impact.
Ability to independently lead AI initiatives from problem definition through to production deployment.
Demonstrated ability to tackle real-world production implementations and challenges.

Preferred Qualifications:

Experience with cloud platforms such as AWS, Azure, or GCP.
Familiarity with MLOps practices and CI/CD pipelines.
Knowledge of model monitoring and evaluation frameworks for sustained performance.
Background in building Agentic AI systems and knowledge of financial technology applications.
Experience in fine-tuning open-source LLMs for diverse applications.