AI Engineer

Job Description

We are seeking an Information Security Specialist – AI Detection Engineer to support enterprise Agent security, detection engineering, and Agent Security operations improvement. This role will help develop and maintain effective Agentic security detections, improve alert quality, support threat detection activities, and contribute to the overall maturity of Agentic security monitoring capabilities.

The successful candidate should have a strong understanding of Agentic AI architectures large language models (LLMs), detection engineering principles, practical experience with SIEM platforms, and familiarity with cloud, identity, endpoint, and network security concepts. The role requires hands-on experience with Python, Microsoft Sentinel and the Microsoft security ecosystem, along with working knowledge of Splunk. The candidate will analyze AI security telemetry, investigate emerging LLM attack techniques, optimize detection quality, and collaborate with security operations, threat intelligence, and engineering teams to improve detection coverage and response effectiveness.

Experience with Microsoft Copilot, Azure AI Foundry, Amazon Connect, Sierra Connect, OpenAI Platform and AI Security technologies is a plus. Experience with applying machine learning and data science techniques to cybersecurity problems is an asset.

Key Responsibilities

• Design, develop, and maintain enterprise AI Agent security detections using Microsoft Sentinel, Microsoft Defender, Splunk, and other security platforms.
• Engineer and optimize detection logic for AI-specific threats, including prompt injection, jailbreak attempts, model misuse, autonomous agent abuse, data exfiltration, and adversarial AI attacks.
• Analyze security telemetry from AI agents, LLM applications, cloud services, endpoints, identities, APIs, and enterprise security controls.
• Continuously tune detections to improve alert fidelity, reduce false positives, and increase detection coverage.
• Research emerging AI threats, attack techniques, and vulnerabilities impacting agentic AI and LLM-based applications.
• Apply cybersecurity knowledge across identity, endpoint, cloud, network, email, and application security domains.
• Collaborate with SOC, incident response, security engineering, and technology teams to understand monitoring needs and improve security outcomes.
• Document AI detection logic, assumptions, data sources, tuning decisions, and investigation guidance in a clear and maintainable way.
• Support ongoing assessment of AI detection effectiveness, including relevance, actionability, coverage, and operational value.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Cybersecurity, Information Security, Data Science, Artificial Intelligence, or a related discipline.
• 5+ years of experience in cybersecurity, detection engineering, security analytics, or security operations.
• Strong understanding of agentic AI, large language models (LLMs), retrieval-augmented generation (RAG), and modern AI application architectures.
• Hands-on experience with Microsoft Sentinel, Microsoft Defender, and the Microsoft Security ecosystem.
• Working knowledge of Splunk and SIEM detection engineering.
• Strong programming skills in Python and experience writing SPL/KQL
• Understanding of cloud security concepts across Microsoft Azure and enterprise cloud environments.
• Knowledge of identity, endpoint, network, and API security principles.
• Experience investigating security alerts and tuning detection logic.
• Excellent analytical, problem-solving, and communication skills.

Preferred Qualifications

• Experience with Microsoft Copilot, Azure AI Foundry, Azure OpenAI Service, or enterprise AI platforms.
• Knowledge of AI security frameworks such as OWASP Top 10 for LLM Applications, MITRE ATLAS, and the NIST AI Risk Management Framework.
• Experience detecting prompt injection, indirect prompt attacks, model manipulation, AI agent abuse, or AI data leakage.
• Familiarity with machine learning workflows, anomaly detection, and data science techniques.
• Experience with Microsoft Defender XDR, Defender for Cloud, Microsoft Purview, or Microsoft Security Copilot.
• Security certifications such as CISSP, GIAC, Azure Security Engineer Associate, SC-200, SC-100, or AI-related certifications.
• Experience developing detection-as-code, security automation, or threat hunting capabilities.
• Experience working in a regulated, financial services, or large enterprise environment.