AI Engineer – NLP, Python

Responsibilities

• Design, build, and enhance AI/NLP solutions including:

- Clause extraction from unstructured documents.
- Semantic comparison against standard/reference clauses.
- Risk identification and classification.

• Process and analyze unstructured financial and legal documents (Word, PDF, scanned files), including multilingual content (e.g., German and English).
• Develop and finetune semantic similarity and embedding‑based models to detect contextually similar clauses with different wording.
• Support creation and maintenance of a structured clause and policy repository aligned to Organization’s standards (e.g., trade finance guarantees).
• Collaborate closely with Organization’s SMEs, product owners, and compliance stakeholders to translate business and regulatory requirements into AI logic.
• Implement explainable AI approaches to ensure traceability and auditability of AI‑generated outputs.
• Support POC development, client demos, and iterative refinements based on the feedback.
• Expose AI capabilities through secure APIs and integrate with downstream systems as required.
• Ensure adherence to data privacy, confidentiality, and secure coding standards expected in a Tier‑1 bank environment.

Skills Requirement

• Bachelors degree in Engineering/Information Technology/Computer Science or a related field.
•  6-8 years of experience in relevant field.
• Hands‑on expertise in NLP, semantic search, and document intelligence, with a strong emphasis on accuracy, explainability, and regulatory compliance, in line with Organization’s risk and governance standards.

Technical Skills

Programming: Strong proficiency in Python, Doc AI, Vertex AI

NLP / GenAI

• Text preprocessing, embeddings, semantic similarity.
• Transformer‑based models and LLMs.
• Prompt engineering and controlled generation techniques.

Frameworks & Libraries

• Hugging Face, spaCy, NLTK
• PyTorch or TensorFlow
• Scikit‑learn

Document Intelligence: PDF / Word parsing, OCR integration for scanned documents.

Backend & Integration: REST API development using FastAPI / Flask.

Data Handling: Working with structured and unstructured datasets.

Version Control: Git, basic CI/CD exposure.