Senior AI Engineer

KEY RESPONSIBILITIES
1. AI Vision and Enterprise Strategy
Define TAC’s 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 TAC’s 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 TAC’s 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 TAC’s 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 TAC’s 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 TAC’s 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.