Position Description:
Responsibilities
Direct Responsibilities
. Collaborate with business stakeholders to understand requirements and identify opportunities for AI‑driven solutions.
. Take ownership of prototyping and productizing AI use cases using our in‑house LLMs.
. Design, develop and deploy Retrieval‑Augmented Generation (RAG) pipelines to improve document search, customer support, compliance, or similar workflows.
. Implement and evaluate classification systems for use cases such as email classification, transaction categorization, risk scoring, etc.
. Analyze and prepare data, perform text extraction, feature engineering and annotation work as required.
. Work with engineering teams to integrate solutions into production environments.
. Document models, workflows and best practices for future projects.
. Stay up‑to‑date on developments in GenAI, NLP and data‑science methods.
Contributing Responsibilities
. Contribute towards innovation; suggest recent practices to be investigated.
. Contribute towards initiatives to improve processes and delivery.
Technical & Behavioral Competencies
. Proficiency in Python programming (Python 3.x).
. Experience with data‑science tools: Jupyter Notebooks, Pandas, NumPy, Scikit‑learn.
. Database knowledge (relational and NoSQL).
. Understanding of NLP fundamentals; text‑processing using HuggingFace, Transformers, spaCy.
. Foundational knowledge of LLMs (prompt engineering, fine‑tuning basics) and their banking use‑cases.
. Understanding of vector databases (FAISS, Chroma), embedding models, indexing and connecting retrieval to LLMs.
. Knowledge of data‑engineering principles, data warehousing, data governance and data quality.
. Experience with data cleaning, preprocessing, feature engineering, handling missing data, normalisation and transformation.
. Familiarity with data‑storage solutions (data lakes, warehouses, cloud‑based storage).
. Knowledge of CI/CD pipelines and tools (Jenkins, GitLab CI/CD).
. Exposure to deploy
📌 Automation & Tooling (Mumbai)
🏢 CGI
📍 Mumbai