Job
Description
Sr Director/ VP AI & Machine Learning – Strategy Overview The next evolution of AI-powered cyber defense is here. With the rise of cloud and modern technologies, organizations struggle with the vast amount of data and thereby security alerts generated by their existing security tools. Cyberattacks continue to get more sophisticated and harder to detect in the sea of alerts and false positives. According to the Forrester 2023 Enterprise Breach Benchmark Report, a security breach costs organizations an average of $3M and takes organizations over 200 days to investigate and respond. AiStrike’s platform aims to reduce the time to investigate and respond to threats by over 90%. Our approach is to leverage the power of AI and machine learning to adopt an attacker mindset to prioritize and automate cyber threat investigation and response. The platform reduces alerts by 100:5 and provides detailed context and link analysis capabilities to investigate the alert. The platform also provides collaborative workflow and no code automation to cut down the time to respond to threats significantly. We are looking for a forward-thinking Leader for AI to define and lead the AI and ML strategy for our next-generation cybersecurity platform. This role sits at the intersection of data science, cybersecurity operations, and product innovation, responsible for transforming security telemetry into intelligent workflows, automated decisions, and self-improving systems. You will lead the vision and execution for how classification, clustering, correlation, and feedback loops are built into our AI-powered threat investigation and response engine. Your work will directly impact how analysts investigate alerts, how automation adapts over time, and how customers operationalize AI safely and effectively in high-stakes security environments. Key Responsibilities ● Define the AI Strategy & Roadmap: Own and drive the strategic direction for AI/ML across investigation, prioritization, alert triage, and autonomous response. ● Architect Feedback-Driven AI Systems: Design scalable feedback loops where analyst input, alert outcomes, and system performance continuously refine models. ● Operationalize ML for Security: Work with detection engineering, platform, and data teams to apply clustering, classification, and anomaly detection on massive datasets—logs, alerts, identities, cloud events—not images or media. ● Guide Complex Security Workflows: Translate noisy, high-volume telemetry into structured workflows powered by AI—spanning enrichment, correlation, and decisioning. ● Collaborate Across Functions: Partner with product managers, detection engineers, threat researchers, and ML engineers to define use cases, data needs, and modeling approaches. ● Ensure Explainability and Trust: Prioritize model transparency, accuracy, and control—enabling human-in-the-loop or override in high-risk environments. ● Lead AI Governance and Deployment Frameworks: Define policies, versioning, validation, and release processes for customer-safe AI usage in production environments. Requirements ● 10+ years of experience in data science, applied ML, or AI product leadership, with at least 3–5 years in cybersecurity, enterprise SaaS, or complex data domains. ● Demonstrated experience applying classification, clustering, correlation, and anomaly detection on structured/semi-structured data (e.g., logs, alerts, network events). ● Strong understanding of cybersecurity workflows: detection, investigation, triage, threat hunting, incident response, etc. ● Experience in building data feedback pipelines or reinforcement learning-like systems where user input improves future predictions or decisions. ● Proven ability to scale AI/ML systems across multi-tenant environments or customer-facing platforms. ● Familiarity with platforms such as Snowflake, Google Chronicle, Sentinel (KQL), or SIEM/SOAR tools is a strong plus. ● Exceptional communication and storytelling skills: able to communicate AI strategy to technical and executive stakeholders alike. ● Experience with security-specific ML tooling or frameworks (e.g., security data lakes, Sigma correlation engines, MITRE ATT&CK mapping). ● Prior work in multi-modal learning environments (signals from logs, identity, cloud infra, etc.). ● Deep familiarity with model evaluation, drift detection, and automated retraining in production settings. ● Exposure to or leadership in building agentic AI workflows or co-pilot-style assistant models in the security space. AiStrike is committed to providing equal employment opportunities. All qualified applicants and employees will be considered for employment and advancement without regard to race, color, religion, creed, national origin, ancestry, sex, gender, gender identity, gender expression, physical or mental disability, age, genetic information, sexual or affectional orientation, marital status, status regarding public assistance, familial status, military or veteran status or any other status protected by applicable law. Show more Show less
