About the role
Responsibilities:
- Setting the technology strategy from a blank page, owning the roadmap for Fraud, Financial Risk, AML, AI workflows, tooling, and automation across Ongoing Monitoring, with the autonomy to decide what gets rebuilt and how.
- Putting agentic AI into production, not a slide deck, building autonomous, multi-agent workflows that investigate alerts, pull external data, chain complex reasoning, and make initial risk calls in real time.
- Staying ahead of adversaries who are also using AI, building detection for bot swarms, deepfake-powered KYC bypass, and algorithmic fraud loops, against a landscape that's constantly shifting: impersonation scams, APP fraud, account takeover, banking fraud.
- Making high-stakes AI defensible, ensuring every system is auditable, explainable, and aligned with global AML directives and data privacy standards, because these decisions carry real regulatory weight.
- Building engineering organisations across India, Eastern Europe, and the UK, an inclusive, high-performance culture that's yours to shape.
- Making the ML lifecycle faster and sharper, partnering with Product, Data, AI, Risk, and Ops to improve predictive modelling and agentic AI capabilities, cutting retraining and rules-deployment time.
- Turning automation into real savings championing data-driven decisions and AI/ML opportunities that cut operational cost and friction at scale.
Requirements:
- 15+ years of engineering experience with 5+ years in leadership roles (Director/Senior Director level).
- Machine Learning: Strong experience in supervised and unsupervised models, decision trees, neural networks, and Large Language Models (LLMs).
- Agent Frameworks: Hands-on experience with multi-agent orchestration frameworks (e. g., LangGraph, AutoGen) used to build self-correcting compliance workflows.
- Fintech Domain Knowledge: Deep understanding of fraud vectors (e. g., mule accounts, account takeovers, synthetic identity fraud) and AML typologies.
- Adversarial AI Security: Proven track record in detecting deepfakes, synthetic identities, and prompt injection attacks targeting financial systems.
- Risk/Scale: Minimum 5+ years building and deploying production-grade, risk-scoring environments at scale.
- Experience with fintech platforms - risk/compliance tooling (AML, Fraud, Financial Risk, SARs, KYX, agentic AI detections).
- Excellent people leadership skills - you know how to grow and inspire teams.
- Solid technical foundations: cloud-native architectures, microservices, event-driven systems, and data platforms (AWS or GCP).