Teams at Hudson Information Technology and Manpower Services

Designs and maintains scalable ETL/ELT pipelines, data warehouses, lakes, and models for analytics, business intelligence, and AI/ML initiatives. Ensures data quality, governance, integrity, and security while optimizing SQL and processing performance. Collaborates with analysts, data scientists, and application teams to support Capital Markets, Fraud Screening, and Financial Crimes use cases. Requires strong Python, Snowflake, SQL, cloud platform, data integration, and financial domain expertise. The role is onsite in New York, NY.

Leads roadmap, backlog, requirements, prioritization, Agile ceremonies, and release planning for an LLM-based application-security platform. Partners with Engineering, AI/ML, AppSec, DevSecOps, Risk, Compliance, and leadership to deliver vulnerability scanning and developer-security capabilities. Defines AI evaluation metrics, testing standards, security workflows, integrations, governance requirements, and product adoption measures while driving improvements based on user feedback, security findings, and model performance.

Design and build enterprise-scale agentic AI platforms supporting multi-agent orchestration, memory, RAG, knowledge graphs, governance, observability, security, evaluation, and cost attribution. Develop scalable API-driven, cloud-native AI services with Azure technologies, event-driven architectures, messaging, monitoring, and responsible AI controls. Partner across business domains to establish agent onboarding, lifecycle management, operational controls, and reliable autonomous workflows.