Description

Key Responsibilities

Design and develop advanced threat detection rules, analytics, and monitoring capabilities.

Perform threat hunting and identify suspicious activity across enterprise environments.

Develop detection content using Splunk, Sentinel, QRadar, or similar SIEM platforms.

Work with SOC, Cyber Defense, and Threat Intelligence teams to improve detection coverage.

Develop AI agents and agentic workflows, including ReAct and multi-agent orchestration.

Integrate AI agents with enterprise platforms such as Jira, ServiceNow, Git, and APIs.

Build and optimize RAG pipelines using vector databases, embeddings, document chunking, indexing, and retrieval techniques.

Develop AI-powered enterprise knowledge solutions such as AI copilots, knowledge assistants, and FAQ solutions.

Evaluate AI applications for functional correctness, response quality, hallucinations, and reliability.

Work with AI evaluation frameworks such as RAGAS, DeepEval, or custom evaluation frameworks.

Build scalable APIs and services using Python, FastAPI, Flask, or similar technologies.

Implement monitoring, observability, performance optimization, and reliability for AI systems.

Apply cybersecurity principles to AI/LLM applications and AI-enabled environments.

Required Qualifications

14+ years of overall cybersecurity / security engineering experience.

Strong hands-on experience with SIEM and threat detection engineering.

Experience with Splunk, Sentinel, QRadar, or equivalent SIEM platforms.

Strong knowledge of threat hunting, incident response, and detection methodologies.

Experience with EDR, cloud security, and MITRE ATT&CK.

Hands-on experience with Python and API/service development.

Experience with Generative AI, LLMs, RAG, or Agentic AI.

Experience with AI evaluation, testing, or monitoring is highly valuable

Key Skills

Education

Bachelor's degree