AI Specialist

AI Technical Expert responsible for enterprise-wide technical leadership in GenAI/LLMs and ML platforms—owning standards and reference architectures, guiding cross-team technical decisions, and driving end-to-end delivery of production AI solutions. The role also leads MLOps/LLMOps practices (DSLC, CI/CD, monitoring, and production governance) and ensures responsible AI through security/privacy controls, mentoring, and global stakeholder engagement.

Job Description:

Responsibilities:

• Own enterprise AI/GenAI technical direction: define standards, reference architectures, and best practices; lead design/architecture reviews and cross-team decisions.
• Drive end-to-end delivery of AI solutions: translate business needs into scalable ML/LLM designs; guide build, evaluation, deployment, and iteration in production.
• Lead platform & operations maturity (MLOps/LLMOps): establish DSLC lifecycle, CI/CD, monitoring/observability, incident practices, and production governance (SLOs, drift, reliability).
• Ensure governance and responsible AI: partner with security/privacy/compliance to implement controls for safety, privacy, auditability, and risk management.
• Enable the organization: mentor engineers and data scientists, build reusable assets, and influence global stakeholders through clear technical communication.

Requirements:

• 12+ years of experience delivering production ML/AI solutions, including GenAI/LLMs, deep learning, and applied statistics.
• Strong proficiency in Python (R is a plus) and hands-on experience with NLP/LLMs; exposure to computer vision is a plus.
• Experience owning or influencing enterprise standards, reference architectures, and cross-team technical decisions (design reviews, architecture boards, etc.).
• Proven experience with MLOps/LLMOps: DSLC lifecycle, CI/CD, model/prompt versioning, monitoring/observability, and production governance.
• Familiarity with cloud platforms and modern AI frameworks; ability to optimise solutions for cost, latency, reliability, and scalability.
• Working knowledge of security, privacy, and responsible AI controls in enterprise environments.
• Strong analytical/problem-solving skills, stakeholder management, and ability to mentor teams and influence globally.