.png){kind=logo}
Vetted Fraud Detection Professionals
Pre-screened and vetted.
Senior Software Engineer specializing in distributed backend services and data pipelines
Mid-Level Backend Software Engineer specializing in FinTech and data pipelines
Mid-level Data Scientist specializing in ML, NLP, and fraud/anomaly detection
Mid-Level Software Engineer specializing in cloud-native microservices and AI/ML
Mid-level Machine Learning Engineer specializing in NLP, federated learning, and fraud detection
Senior Full-Stack Software Engineer specializing in banking platforms on AWS
Engineering Manager and Staff Software Engineer specializing in ML platforms and FinTech risk
Mid-level Machine Learning Engineer specializing in fraud prevention and LLM systems
Senior Data Analytics & Applied ML Engineer specializing in LLMs, RAG, and MLOps
Executive Data & AI Leader specializing in enterprise data platforms and multi-cloud transformation
Mid-level Full-Stack Developer specializing in cloud-native apps, AI/ML, and microservices
Junior AI/ML Engineer specializing in LLMs, RAG, and document intelligence
Mid-level Python Backend Developer specializing in FinTech and ML-driven fraud detection
Mid-level Full-Stack Engineer specializing in Python microservices and cloud automation
Executive Engineering Leader specializing in cloud platforms, infrastructure, and SRE
Sharath Nyalakonda
Mid-level AI/ML Engineer specializing in NLP, graph models, and MLOps for FinTech and Healthcare
“AI/ML engineer who has deployed production LLM/transformer-based systems for merchant intelligence and fraud/support optimization, delivering +27% merchant engagement and +18% payment success. Deep experience in privacy-preserving, PCI DSS-compliant data/ML pipelines (Airflow, AWS Glue, Spark, Delta Lake) and scalable microservices on Kubernetes, plus proven cross-functional delivery in healthcare claims analytics at UnitedHealth Group (12% HEDIS claim reduction).”
Travis Johnson
Senior Full-Stack Software Engineer specializing in FinTech payments and fraud systems
“Backend/data engineer with production experience building credit/fraud enrichment services and checkout pipelines on AWS (EKS + Lambda) using FastAPI, Kafka, Postgres, and Redis, with a strong focus on reliability patterns (timeouts/retries/circuit breakers) and observability. Has also built AWS Glue/PySpark ETL into S3/Redshift with schema evolution and data quality controls, and modernized legacy credit decisioning into Java/Node microservices with parallel-run parity validation and feature-flag rollouts.”