Information Protection Engineer

About the Role The Artificial Intelligence and Data Science Engineer is a senior, hands-on technical position responsible for designing, building, and operationalizing AI, machine learning, and advanced analytics solutions that strengthen the organization's cybersecurity defense posture. You will apply modern AI, agentic systems, machine learning, and quantitative analytics to enterprise security telemetry-delivering scalable, production-ready solutions that support threat detection, automation, and cyber risk insights. This role partners closely with cybersecurity operations, data engineering, cloud engineering, and platform teams to drive measurable, data-driven security outcomes., Key Responsibilities Design, develop, and deploy ML models and advanced analytics for cybersecurity use cases (e.g., threat detection, anomaly detection, predictive risk analysis) Build AI-driven automation and generative-AI-based capabilities for investigation, triage, and reporting Analyze and model large-scale enterprise, cloud, identity, and endpoint security data Create metrics, dashboards, and data products that support security operations and leadership decision-making Ensure all AI and data solutions adhere to secure engineering, privacy, and regulatory standards Collaborate with cybersecurity, IT, data engineering, and cloud teams to integrate ML and analytics solutions into enterprise workflows Serve as a senior technical contributor and mentor, promoting best practices in AI, data science, and secure engineering

Minimum Qualifications AI & Engineering Experience Agentic AI frameworks (Vertex), MCP, multi-agent orchestration LLM APIs, Retrieval-Augmented Generation (RAG) Strong Python and SQL development skills Production deployment of ML/analytics solutions Data Science & Data Engineering Lakehouse Architecture, Delta Lake, Apache Iceberg Snowflake, Databricks, BigQuery Airflow, ETL pipeline design Quantitative analysis and statistical modeling Power BI (dashboarding and insights)

Required Qualifications 5+ years in cybersecurity, data science, machine learning, analytics, or related technical domains Experience with security telemetry and platforms (SIEM, EDR, cloud security, identity systems) Strong understanding of cybersecurity concepts, threat landscapes, and defensive technologies Demonstrated success bringing ML/analytics projects into production at scale

Preferred Qualifications Experience using generative AI or advanced automation in security or operational contexts Familiarity with major cloud platforms (Azure, AWS, Google Cloud Platform) Knowledge of cybersecurity frameworks (NIST, MITRE ATT&CK, Zero Trust) Relevant certifications (security, cloud, AI/ML) Financial services industry experience