Lead AI/ML Engineer Regulatory Reporting - Senior Vice President
Posted May 6, 2026
Key Responsibilities:
-
Build unsupervised and semi-supervised ML models such as Isolation Forests and Autoencoders to identify outliers in millions of transactional records. - Go beyond simple "threshold checks" and detect complex patterns to ensure accurate anomaly detection. - Reduce false positives to establish trust in model alerts within the Reporting Team. - Design RAG pipelines to extract key regulatory attributes from unstructured data like Credit Agreements and Loan Docs. - Develop "Agentic" workflows where GenAI suggests mapping logic and identifies root causes, requiring validation from human SMEs. - Ensure Explainability (XAI) in every model output, providing reasoning behind alerts. - Create Validation Interfaces using Streamlit or React for business users to validate model predictions against source documents. - Collaborate with Model Risk Management (MRM) on validation frameworks for non-deterministic GenAI models. - Lead and mentor a team of 4-5 junior data scientists/engineers in Mumbai. - Act as an "AI Evangelist" to demonstrate the benefits of AI to Operations/Finance teams. Qualification Required:
-
8+ years of experience in Data Science/Engineering with expertise in Scikit-learn, TensorFlow, or PyTorch. - Hands-on experience with LLM orchestration frameworks like LangChain and Vector Databases such as Pinecone, Milvus, or pgvector. - Proficiency in building tools like Streamlit or Gradio for rapid prototyping of human-review interfaces. - Experience in Financial Services, particularly in Fraud Detection, AML, or Risk Modeling. - Ability to effectively communicate complex technical concepts, such as "Hallucination Risk," to non-technical stakeholders. Role Overview: You will be part of a specialized AI/ML team in Mumbai focused on modernizing the Regulatory Reporting function. Your primary responsibility will be to build and deploy Anomaly Detection Models and GenAI Workflows to enhance data quality and automate manual processes. A key aspect of your role will be solving the "Validation Bottleneck" by designing workflows that facilitate easy validation of model outputs by business users. Key Responsibilities: