Senior Insider Risk & AI Security Analyst​/Engineer IV

Position

Schedule:

Full-Time

This job posting is anticipated to remain open for 30 days, from 11-May-2026. The posting may close early due to the volume of applicants.

The Digital Insider Risk (DInR) Department protects The Jones Financial Companies, and its subsidiaries (collectively, "the Firm") against risk stemming from user digital activity. The Digital Insider Risk and Data Loss Prevention (DLP) Analyst will be responsible for monitoring, analyzing, investigating and reporting of User Behavior Analytics and Data Loss Prevention alerts across various tools, ensuring the protection of client and Firm data.

You will work closely with security analysts, engineers, and other IT professionals to enhance our security posture through the development and refinement of detection and enforcement rules.

In addition, this role will support the Firm's emerging use of Artificial Intelligence and machine learning technologies by providing AI observability and risk oversight. This includes monitoring user interactions with AI systems, identifying potential misuse or data exposure, and partnering with engineering and risk teams to ensure AI systems operate securely, responsibly, and in alignment with Firm policies.

• Monitor and investigate user activity involving AI-enabled tools (e.g., generative AI platforms, AI copilots, internal ML systems) to identify potential data leakage, policy violations, or misuse.
• Develop and maintain AI observability use cases to increase visibility into how AI systems are accessed, used, and abused across the Firm.
• Assess AI telemetry, logs, and metadata to understand data flows, user behavior patterns, and abnormal or risky AI usage.
• Partner with engineering and platform teams to define logging, monitoring, and alerting requirements for AI systems.
• Support AI governance initiatives by mapping observed AI usage to Firm policies, data classification standards, and insider risk indicators.
• Monitor, triage, investigate, and elevate UEBA and DLP alerts from multiple systems (e.g., Gurucul, XSOAR, Microsoft Purview, Proofpoint, Zscaler).
• Lead high-priority incident response activities related to insider risk and critical data exfiltration events.
• Perform initial analysis of data from a variety of sources (to include but not limited to host, network, cloud, messaging, application), correlating it to meaningful DLP and Insider Risk events.
• Support confidential and complex digital investigations.
• Generate informed reporting around security events and metrics.
• Document investigations in adherence to all audit and legal requirements.
• Support the development of documentation in support of response processes and/or procedures.
• Analyze incidents for patterns of data misuse or exfiltration across email, endpoints, cloud, and web.
• Provide mentorship and guidance to junior analysts, fostering a culture of continuous learning and professional development.

Edward Jones' compensation and benefits package includes medical and prescription drug, dental, vision, voluntary benefits (such as accident, hospital indemnity, and critical illness), short- and long-term disability, basic life, and basic AD&D coverage. Short- and long-term disability, basic life, and basic AD&D coverage are provided at no cost to associates. Edward Jones offers a 401k retirement plan, and tax-advantaged accounts: health savings account, and flexible spending account.

Edward Jones observes ten paid holidays and provides 15 days of vacation for new associates beginning on January 1 of each year, as well as sick time, personal days, and a paid day for volunteerism. Associates may be eligible for bonuses and profit sharing. All associates are eligible for the firm's Employee Assistance Program.

Hiring Minimum: $101700

Hiring Maximum: $173200

• Minimum of 5 years in Information Systems Security or Information Technology with a focus on security controls and processes.
• Experience analyzing or monitoring AI, machine learning, or automation platforms from a security, risk, or governance perspective.
• Familiarity with generative AI concepts (e.g., prompt-based interactions, training vs. inference, data grounding, embeddings).
• Understanding of AI-related risk domains such as data leakage, hallucinations, model misuse, and insider-driven abuse.
• Experience working with telemetry, logs, or behavioral data from AI-enabled applications or cloud services.
• Ability to translate technical AI risks into clear, actionable insights for security leaders, risk partners, and business stakeholders.
• Possession of a recognized, advanced security certification.
• Proven ability to define and utilize UEBA models to detect complex, non-signature based risks.
• Experience triaging, investigating and assisting remediation of security alerts.
• Familiarity with various cybersecurity tools and how to leverage them effectively (e.g. SIEM, SOAR, UEBA, DLP).
• Familiarity with enterprise data types and sensitivity levels: PII, PHI, PCI, IP,…