General Description:
The AI Cyber Defense Engineer - Emerging Risks is responsible for helping design, build, test, implement, and continuously improve AI-driven cyber defense capabilities with a primary focus on threat detection, prevention, response, and remediation.
This role combines hands-on engineering, adversarial thinking, and applied AI/ML expertise to enhance the organization's ability to identify, withstand, and respond to cyber threats in near real time. The engineer will operationalize AI use cases across security tooling and platforms while ensuring solutions are resilient, explainable, and aligned with enterprise risk management objectives
Essential Duties and Responsibilities: - AI-Enabled Cyber Defense and Emerging Threats
- Support the design, testing, and implementation of AI-enabled cyber defense capabilities across prevention, detection, protection, response, and remediation.
- Evaluate emerging AI, machine learning, automation, and analytics tools for practical cybersecurity use cases.
- Assess how threat actors may use AI to accelerate reconnaissance, social engineering, vulnerability discovery, exploitation, malware generation, credential attacks, and evasion techniques.
- Develop defensive AI use cases that improve threat detection, anomaly analysis, attack path mapping, control validation, incident triage, and remediation decisioning.
- Contribute to the organization's broader strategy for emerging cyber risks, including AI-enabled threats, autonomous agents, quantum-related risks, supply chain compromise, and advanced offensive cyber techniques.
- Threat Detection, Protection, and Control Enhancement:
- Analyze security telemetry, threat intelligence, endpoint data, network activity, cloud signals, identify data, and application indicators to identify opportunities to strengthen cyber defenses.
- Develop or enhance detection logic, monitoring approaches, alerting rules, threat hunting queries, response playbooks, and protective controls
- Apply threat-informed defense concepts, including MITRE ATT&CK, adversary tactics, exploit trends, and common attack paths.
- Exposure, Misconfiguration, and Vulnerability Risk Reduction:
- Use AI, automation, and data analysis to identify, prioritize, and support remediation of high-risk exposures, misconfigurations, vulnerabilities, and control gaps.
- Correlate security findings with asset criticality, business impact, exploitability, threat intelligence, exposure, compensating controls, and regulatory relevance.
- Analyze data from scanners, SIEM, EDR, cloud platforms, CMDBs, APIs, ticketing systems, threat intelligence sources, and raw data files to support risk-based decision-making.
- Recommend appropriate remediation, mitigation, monitoring, isolation, or risk treatment options based on technical feasibility and business context.
- Security Engineering, Automation, and Stakeholder Enablement
- Build scripts, integrations, dashboards, automation workflows, and analytical models that improve cyber defense operations, reduce manual effort, and improve risk-based decision making
- Evaluate and tune security tools to improve effectiveness, reduce noise, and generate actionable outputs for technical teams.
- Partner with cross-functional stakeholders (Enterprise Architecture, Cloud Platform, DevSecOps, and business/operational teams) to scale cyber defense capabilities without creating unnecessary operational burden.
Education Bachelor's degree in Cybersecurity, Computer Science, Engineering, Data Science, or a related field
Required Qualifications:- 5+ years of experience in cybersecurity, security engineering, application security, infrastructure security, or related fields.
- 1+ years of hands-on experience with enterprise AI platforms or frameworks such as AWS Bedrock, OpenAI APIs or similar.
- Strong knowledge with cloud environments (AWS, Azure)
- Strong understanding of vulnerability management, exploitability analysis, threat intelligence, attack paths, security controls, and risk-based remediation
- Hands-on experience with endpoint security, SIEM tools, SOAR, EDR, cloud/application/infrastructure security tools
- Working knowledge of AI, machine learning, LLMs, agentic AI concepts, or AI-assisted security tools, with the ability to evaluate their practical use in cyber defense.
- Experience using scripting, automation, and data analysis to solve security problems
Preferred Qualifications: - Experience in financial services, banking, or another regulated industry
- Experience with security tools such as Tenable, Microsoft Defender, Splunk, Sentinel, Zscaler, ServiceNow, Veracode or similar
- Knowledge of how AI frontier models work for cyber security defense
- Experience with cloud platforms, container environments, CI/CD pipelines, identity platforms, network segmentation, zero trust, endpoint hardening, or cryptography
Other Competencies: - Security engineering mindset with the ability to build, integrate, automate and improve cyber defense capabilities
- Practical understanding of both offensive and defensive cybersecurity
- Ability to work creatively within constrained environments, including legacy systems, vendor limitations, complex dependencies, and competing operational priorities
- Strong judgement in determining when to remediate, mitigate, monitor, isolate, escalate or accept residual risk.
- Comfortable operating in emerging technology areas where standards and playbooks are still evolving
- Ability to evaluate AI-generated output critically and avoid overreliance on unvalidated automation
Important: The candidate must provide evidence of academic preparation or courses related to the job posting, if necessary.
Our hybrid work model benefit applies to certain positions and is subject to changes based on the organizational needs.
