Manager, Cyber Research

The Security Research Team powers Axonius Exposures by designing the analytical, exposure management, and data pipelines that drive product capabilities, including risk scoring, data modeling, and LLM-driven reasoning. Operating in close partnership with Product and Engineering, team members own projects end-to-end from problem definition to validated production prototypes. We are seeking a Group Manager to lead, mentor, and grow this team while driving portfolio prioritization, technical rigor, and cross-functional execution across complex cybersecurity and data-heavy initiatives.

Responsibilities

• Manage, coach, and grow a team of 4 to 8 security researchers, taking direct accountability for hiring, performance management, and research output quality.

• Drive cross-functional delivery with Product and Engineering leaders, translating business requirements into clear research scope, project timelines, and scalable production prototypes.

• Review and critically evaluate complex technical approaches, including data pipeline architecture, exposure/risk scoring logic, mitigation strategies, and LLM pipeline designs (prompting, retrieval, evaluation).

• Lead project portfolio prioritization and represent the team's research roadmap and value metrics directly to executive leadership with minimal top-level intervention.

Minimum Qualifications

• Minimum 5 years of professional experience in cybersecurity, specifically within vulnerability research, exposure/risk scoring, threat intelligence, or adjacent domains.

• Minimum 2 years of direct people management experience leading teams of security researchers or software engineers.

• Hands-on proficiency with Python and SQL for research validation, prototyping, and data analysis.

• Proven track record of cross-functional collaboration with Product and Engineering to ship research-backed data pipelines or cybersecurity capabilities into commercial software products.

Preferred Qualifications

• Hands-on experience designing, testing, or deploying LLM-based systems, including retrieval-augmented generation, prompt engineering, and model evaluation metrics.

• Demonstrated experience developing risk scoring models, normalizations, and mitigation strategies across EDR data sources and vulnerability frameworks.

• Experience scaling research teams from mid-size to larger organizational structures while defining operational success metrics.

• Strong technical architecture background with the ability to define handoff specifications for engineering productionization without requiring hands-on daily coding.

• Prior experience in high-growth, enterprise B2B SaaS or cybersecurity vendors.

• Bachelor's or Master’s degree in Computer Science, Cybersecurity, Data Science, or a related quantitative field.

 

 #LI-HYBRID #LI-AZ1