AI/ML Architect - Banking

Responsibilities

• ● We are looking for AI/ML Architect with 10+ years in data and analytics, including 6+ in ML/AI, 3+ in banking and 2+ on production GenAI
• ● Must-have skills
• ● Banking and AI governance
• ● Taking AI/ML solutions to production inside banks through model risk or AI governance review.
• ● Responsible AI: explainability, audit trails, human-in-the-loop controls and model monitoring (e.g. MAS FEAT principles).
• ● Financial crime data: AML models, alerts and case data.
• ● Generative AI architecture
• ● RAG, text-to-SQL over semantic layers, and agentic analytics for insight generation, metadata discovery and query generation.
• ● Integration with enterprise LLM platforms, enforcing entitlements, row-level security and prompt/response audit.
• ● LLM evaluation: accuracy, SQL correctness, hallucination testing and guardrails.
• ● Code intelligence: parsing SQL, PL/SQL, SAS and Python to extract mappings, lineage, dependencies and business rules.
• ● Generating specifications, code and tests from metadata, with traceability.
• ● ML Engineering
• ● Python, Spark, Scala or Java; TensorFlow, PyTorch and scikit-learn.
• ● MLflow, feature engineering, model deployment and monitoring; DataOps practices.
• ● Large-scale data on Hadoop and Lakehouse platforms; semantic layers, knowledge graphs and federated governance.
• ● Delivery and communication
• ● Leading multidisciplinary teams across data engineering, analytics, AI/ML and business domains.
• ● resenting AI designs and controls to model risk, audit and business stakeholders.
• ● Good-to-have skills