Accountabilities:

The AI-focused Incident Response Consultant will contribute to the design and implementation of next-generation security workflows by combining incident response knowledge with AI development practices. The role requires ownership of AI workflow experimentation, evaluation, documentation, and collaboration with cybersecurity stakeholders to create scalable and trustworthy solutions.

• Design, prototype, test, and evaluate AI-powered workflows supporting incident response activities such as alert triage, investigation planning, evidence summarization, enrichment automation, and analyst decision support.
• Develop agentic AI workflows using modern frameworks and approaches, including large language models, retrieval-augmented generation, tool calling, structured outputs, and human-in-the-loop validation.
• Build multi-step AI workflows with appropriate state management, memory handling, guardrails, approval checkpoints, and deterministic routing mechanisms.
• Create evaluation methodologies for AI security workflows, including testing strategies, historical validation, benchmark datasets, error analysis, confidence measurement, and regression testing.
• Support AI workflow observability and governance by implementing tracking for inputs, outputs, model usage, costs, tool interactions, reviewer decisions, and operational outcomes.
• Translate AI prototypes into reliable operational capabilities by documenting assumptions, limitations, failure scenarios, escalation paths, and human oversight requirements.
• Collaborate with security technology teams to integrate AI workflows with platforms such as SIEM, SOAR, EDR, threat intelligence solutions, case management systems, and internal knowledge repositories.
• Analyze security data, investigation artifacts, and historical incidents to improve AI-assisted decision-making and workflow effectiveness.
• Provide technical documentation, analysis reports, and recommendations to support cybersecurity leadership and operational teams.
• Partner with incident response professionals and technology stakeholders to identify opportunities where AI can improve security processes while maintaining investigative rigor.

Requirements:

The ideal candidate combines strong cybersecurity operations experience with practical knowledge of AI workflow development and automation. This professional should be comfortable working with security data, emerging AI technologies, and cross-functional teams to deliver reliable and measurable improvements.

• 7+ years of experience in cybersecurity, preferably within Incident Response, threat detection, security operations, digital forensics, investigations, or threat intelligence.
• Strong understanding of security operations processes, including alert triage, incident investigation, evidence collection, escalation procedures, reporting, and case management.
• Hands-on experience designing, developing, testing, or evaluating AI-assisted workflows, LLM-based applications, automation solutions, or analyst productivity tools.
• Practical understanding of agentic AI concepts, including workflow orchestration, tool calling, multi-step execution, retrieval-augmented generation, prompt engineering, structured outputs, and AI guardrails.
• Experience with AI development frameworks or SDKs such as LangGraph, LangChain, Semantic Kernel, AutoGen, CrewAI, OpenAI Assistants/Agents SDKs, GitHub Copilot SDK, Azure AI Foundry, or similar technologies.
• Ability to contribute to workflow components, scripts, automation logic, prompt templates, evaluation frameworks, and lightweight applications using technologies such as Python, PowerShell, SQL, JSON/YAML, REST APIs, notebooks, and Git workflows.
• Experience working with structured cybersecurity data, including logs, alerts, detection outputs, investigation records, threat intelligence, and historical incident information.
• Familiarity with security platforms such as SIEM, EDR, SOAR, threat intelligence platforms, case management tools, enrichment APIs, and security data repositories.
• Knowledge of AI workflow evaluation practices, including benchmark testing, false positive and false negative analysis, confidence scoring, regression testing, and reliability measurement.
• Strong analytical skills with the ability to critically assess AI-generated outputs, validate conclusions, and identify unsupported or inaccurate results.
• Excellent written and verbal communication skills, with the ability to create technical documentation and communicate findings to both technical and leadership audiences.
• Ability to collaborate effectively with cybersecurity teams, technology partners, governance stakeholders, and subject matter experts.
• Professional security certifications such as CISSP, GCIH, GCFA, GCFE, GCFR, or equivalent are considered a plus.

Benefits:

• Competitive compensation range of $120/hour to $124/hour.
• Fully remote work model.
• Opportunity to work on innovative AI and cybersecurity initiatives with significant operational impact.
• Exposure to advanced AI technologies, agent frameworks, and modern security automation practices.
• Opportunity to collaborate with cybersecurity professionals, technical experts, and technology partners.
• Professional growth through involvement in emerging AI-driven security transformation projects.
• Inclusive workplace environment committed to equal opportunity and diversity.