Define and own the AI Security technology and research roadmap aligned to multi-year TIC objectives.

Lead and govern advanced AI security research spanning model inspection, unlearning, provenance, and compliance assurance.

Act as Chief Architect for AI Security platforms including scanners, verification pipelines, lineage systems, and policy engines.

Drive translation of research outcomes into proofs of concept, benchmarked solutions, and deployable platform components.

Establish technical standards for security claims, verification, benchmarking, and reproducibility.

Provide technical leadership and mentorship to research, engineering, MLOps, and product teams.

Ensure adherence to emerging global AI security standards, regulatory expectations, and compliance requirements.

Lead intellectual property generation and publication in reputed AI and security forums.

Represent in relevant external technical, academic, and industry engagements related to AI security.

EDUCATION & QUALIFICATIONS:

PhD or Master's degree in CS, AI/ML, Crypto, Cybersecurity, or related fields from a premier institute with strong research depth.

REQUIRED SKILLS:

- 15+ years of experience in advanced AI/ML research, security engineering, or deep-tech system architecture.

- Proven experience leading principal-level technical or research initiatives and translating research into real-world systems.

- Deep expertise in Large Language Models, foundation models, fine-tuning, LoRA/adapters, and RAG-based architectures.

- Strong understanding of model internals including weight-space analysis, activation behaviour, and interpretability.

- AI security and forensics: model fingerprinting, backdoor detection, model reuse/derivation analysis, and supply-chain risk.

- Hands-on knowledge of model unlearning techniques, verification methods, privacy assurance, and side-effect control.

- Architecture experience for scalable AI security platforms, including experimentation pipelines, MLOps, APIs, and enterprise deployment.

- Experience across R&D labs, research projects, product companies, AI projects, or enterprise solution ownership.

Musthave Skills:

- LLMs, foundation models, fine-tuning, LoRA/ adapters, and RAG.

- AI security and forensics covering model fingerprinting, backdoor detection, model reuse/derivation analysis, and supply-chain risk.

- Model unlearning, verification, privacy assurance, and side-effect control.

- Scalable AI security platform architecture, MLOps, APIs, experimentation pipelines, and enterprise deployment.

- Principal-level technical/research leadership with research-to-production translation.

Nicetohave Skills:

- Earlier experience as CTO in a similar technology domain.

- Association with or experience involving the premier institutes/research organisations listed in the source JD.

- External technical, academic, or industry engagement through publications, IP creation, and industry impact.