A career across enterprise systems, applied machine learning and bank-grade agentic AI architecture.
Distributed banking, telecommunications and manufacturing systems built on APIs, transaction platforms and enterprise integration.
Distributed systems, APIs, high-throughput transaction processing and enterprise integration established the deterministic systems foundation beneath the later AI work.
Predictive modelling, workforce analytics, segmentation and risk-oriented analytics in financial-services and enterprise settings.
Built and led applied analytics capability, moving from models as experiments to repeatable pipelines and cross-functional adoption.
Deterministic-first workflow placement, reconstructive case state, calibrated routing, tool-use evaluation and governed memory.
Developed deterministic-first placement, reconstructive case state, calibrated routing, tool-use evaluation and governed-memory patterns for regulated workflows and long-horizon agents.
A portfolio spanning more than forty agentic use cases with an engineering ecosystem of more than one hundred people across credit, servicing, fraud, KYC, risk, legal and migration work.
Production and scaling work included credit-memo automation, conversational servicing, perpetual KYC, fraud investigation, document intelligence and control transformation across AWS, Google Cloud and Azure estates.
CTO-level architecture decisions for a shared knowledge and context layer, relationship-manager assistance, financial-crime identity inference and agentic credit refer-back.
The work joined context reconstruction, evidence graphs, deterministic decision services, calibrated residual reasoning, cross-cloud identity and model-risk evidence into reusable platform patterns.
Research on deterministic-first agents, model-risk evidence, governed context, tool use, evaluation and live banking workflows.