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Senior, niche ML/AML role reduces applicant density despite Hyderabad metro and Tide's recognizable fintech brand.
Requires fintech AML, fraud and adversarial AI expertise, limiting cross-industry transferability.
Explicit 15+ years, leadership, and niche ML/AML requirements create highly selective filters.
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Own the technology strategy and roadmap for ongoing monitoring including fraud, financial risk, AML, AI workflows, tooling, and automation.
Lead and grow multiple engineering squads, building scalable AI/ML-driven detection systems to analyze massive transaction volumes and identify adversarial behaviors such as bots and deepfake-based fraud.
Ensure AI systems compliance with AML directives and data privacy, while partnering with Product, Risk, and Operations to enhance predictive ML models and agentic AI capabilities.
15+ years engineering experience with 5+ years in leadership roles at Director or Senior Director level.
Strong expertise in machine learning techniques including supervised/unsupervised models, decision trees, neural networks, and Large Language Models (LLMs).
Hands-on experience with multi-agent orchestration frameworks (e.g., LangGraph, AutoGen) and fintech domain knowledge of fraud vectors and AML typologies.
Proven track record in adversarial AI security detecting deepfakes, synthetic identities, prompt injection attacks; experience with production-grade, risk-scoring environments at scale.
Senior engineering leader with deep fintech risk and compliance domain expertise, especially in AML, fraud, and financial risk tooling.
Experienced in scaling complex AI/ML systems and multi-agent AI workflows in regulated environments.
Demonstrated ability to lead high-performance engineering teams focusing on automation, AI-driven detection, and compliance at scale.