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Vetted Fraud Detection Professionals
Pre-screened and vetted.
Senior Applied Machine Learning Engineer specializing in FinTech & E-commerce
Junior Machine Learning Engineer specializing in fraud detection and healthcare ML
Senior AI/ML Engineer specializing in Generative AI, RAG, and MLOps for FinTech
Andrew Stewart
Senior Software Engineer specializing in Healthcare AI and FinTech platforms
“Google Health engineer who owned and shipped an AI-powered clinical insights dashboard and NLP clinical note extraction service end-to-end (React/Next.js frontend; Python/Node microservices on GKE; TensorFlow transformers; BigQuery analytics). Demonstrated strong production rigor (CI/CD, testing, observability, guardrails for sensitive data) and delivered measurable outcomes including 30% faster diagnostics, 40% less manual documentation, 15% higher adoption, and 25% lower ops costs.”
Senior Full-Stack Software Engineer specializing in cloud, payments, and telehealth
Arijit Das
Executive engineering leader specializing in AI, cloud, and FinTech transformation
“Fintech operator at Upstart with hands-on experience in lending underwriting and verification automations, now developing a fully automated HELOC product aimed at reducing funding timelines from 30-45 days to 5 days. Brings strong market conviction in the HELOC space and has already spoken with fintech investors interested in a white-label solution for banks and credit unions.”
Martin Bom
Director-level Engineering Leader specializing in cloud services and large-scale delivery
“Engineering leader with a hands-on developer background who has launched and scaled cloud services at AWS (CloudShell) while also leading AWS Cloud9. Built multi-year roadmaps and cross-org stakeholder alignment (product/marketing/mobile), and has a track record of scaling teams (3x growth) by implementing operational excellence, automated quality gates, and security champion programs; advocates serverless architectures to minimize maintenance and accelerate global expansion.”
Mid-Level Backend Software Engineer specializing in payments and real-time analytics
Senior Research Scientist specializing in LLM verification and fraud/risk modeling
Senior Full-Stack Engineer specializing in cloud-native and AI-powered enterprise products
Mid-level AI/ML Engineer specializing in LLM infrastructure and FinTech ML platforms
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Mid-level Full-Stack Software Engineer specializing in FinTech analytics and security
Mid-level Software Engineer specializing in event-driven backend and AI-enabled systems
Senior Full-Stack Software Engineer specializing in FinTech payments and risk systems
Senior Software Engineer specializing in payments, billing, and fraud/risk platforms
Senior Data Engineer specializing in cloud-native data platforms and streaming pipelines
Senior AI/ML Engineer specializing in LLM agents, RAG, and production ML systems
Executive CTO and serial founder specializing in AI platforms and Financial Services
Thazim Banu Shaffee
Engineering Manager specializing in payments, risk, and high-scale distributed systems
“Engineering leader/player-coach on a risk core transaction platform (payments/branded checkout) who led major migrations from a monolithic stack to microservices, including API contract redesign and performance improvements (reported ~500ms latency reduction). Experienced running high-stakes production incidents (upgrade-related outage/degradation) end-to-end with RCA and rollout-process changes, and has accelerated delivery via documentation/tooling (audit sign-off cycle reduced from ~3 sprints to ~1).”
Thomas Baker
Senior Full-Stack Engineer specializing in serverless AWS and event-driven systems
“Backend/data engineer with experience at AWS and Intuit building and operating production serverless systems and data pipelines. Delivered an internal AWS TV video-processing platform using Step Functions/Lambda/S3/DynamoDB with strong reliability and cost controls, and built Glue-based ETL for compliance/risk events (Kafka to partitioned Parquet). Also modernized legacy compliance systems into Java/Node event-driven services and has demonstrated measurable SQL tuning impact (200s to 20s).”