Senior AI Engineer

KEY RESPONSIBILITIES

1. AI Vision and Enterprise Strategy

• Define TACs multi-year AI roadmap aligned with the 2030 Vision.
• Identify high-impact AI opportunities across vulnerability management, application security, SOC 2 automation, IoT security, and Web3 audits.
• Establish TACs AI leadership position relative to global cybersecurity competitors.

2. AI-Driven Product Innovation

• Lead development of AI-powered cybersecurity capabilities including predictive vulnerability detection, automated remediation, risk scoring, agentic AI workflows, and generative AI for cyber defense.
• Convert prototypes into scalable, revenue-generating enterprise features.
• Collaborate with product and engineering to integrate AI deeply into the ESOF ecosystem.

3. AI Architecture, Data and Infrastructure

• Build TACs end-to-end AI platform including data lakes, pipelines, feature stores, and model-inference systems.
• Ensure distributed, secure, and scalable AI deployment across global customer environments.
• Implement robust ML Ops and production monitoring systems.

4. Governance, Security and Responsible AI

• Establish TACs standards for responsible AI, including model explainability, bias mitigation, privacy, and regulatory compliance.
• Build resilient, enterprise-grade AI systems capable of withstanding adversarial attacks.
• Ensure alignment with global frameworks (ISO, SOC 2, NIST, GDPR, etc.).

5. Leadership, Culture and Talent

• Build and lead a world-class AI organization across ML engineering, data science, infrastructure, and research.
• Drive AI literacy and adoption across the entire company.
• Serve as TACs global spokesperson and internal champion for AI transformation.

6. Partnerships and Ecosystem Expansion

• Develop partnerships with AI labs, cloud hyperscalers, academic institutions, and cybersecurity research bodies.
• Represent TAC at global cybersecurity and AI conferences, industry panels, and policy forums.
• Build TACs external reputation as a pioneer in AI-driven cybersecurity.

IDEAL CANDIDATE PROFILE

Experience

• 5-7 years in AI/ML, with at least 5 years in senior leadership.
• Proven track record deploying AI at scale in cybersecurity, enterprise SaaS, cloud, or regulated sectors.
• Built or led AI teams serving enterprise or government clients.

Technical Expertise

• Generative AI, LLMs, deep learning.
• ML Ops, model governance, inference optimization.
• AI security (adversarial ML, data protection).
• Large-scale data engineering and distributed systems.

Leadership Competencies

• Strategic thinker with strong product and business acumen.
• Exceptional communication with ability to work with Board, C-suite, enterprise clients, and engineering teams.
• Thrives in fast-paced, founder-led, high-growth environments.
• Experience working across global markets (US, EU, Middle East, APAC).

SUCCESS METRICS (KPIs)

• Percentage of TAC products with AI-enabled capabilities.
• Revenue contribution from AI-powered features.
• Reduction in manual processes through automation.
• Accuracy, robustness and security of deployed AI models.
• Speed from prototype to production.
• Team growth, productivity and innovation output.
• Partnerships, patents, awards, and industry recognition.