Director of Artificial Intelligence

Xander Talent · India

Key Responsibilities

AI Solution Architecture

• Design end-to-end AI, ML, GenAI, and Agentic AI architectures aligned to business outcomes.
• Define solution blueprints covering data ingestion, model lifecycle, orchestration, deployment, monitoring, and governance.
• Create architecture patterns and reusable frameworks that accelerate AI delivery.
• Evaluate and select appropriate AI technologies, platforms, and tooling.

Technical Leadership

• Provide architecture leadership across multiple initiatives and delivery teams.
• Guide engineering teams on architectural best practices and AI adoption.
• Support architectural reviews, design governance, and technology decisions.
• Collaborate with Enterprise Architecture and platform teams to align with strategic roadmaps.

Generative AI & Agentic AI

• Design architectures using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, orchestration frameworks, and agent-based systems.
• Define patterns for prompt management, evaluation, observability, and AI safety controls.
• Support the adoption of secure and governed GenAI capabilities across the organisation. [AI Enterpr...ategy v5.1 | PowerPoint], [Build your...n’t sure w | Viva Engage]

Governance, Risk & Security

• Ensure AI solutions comply with Responsible AI, security, privacy, and risk requirements.
• Contribute to model governance, architecture standards, and technical assurance processes.
• Partner with Cyber Security, Risk, and Compliance teams to design secure AI capabilities.
• Embed monitoring, auditability, explainability, and operational controls into AI solutions. [AI Enterpr...ategy v5.1 | PowerPoint]

Stakeholder Engagement

• Translate complex technical concepts into business-friendly language.
• Influence senior technical and business stakeholders.
• Facilitate architecture workshops and solution design sessions.
• Build strong relationships across product, engineering, architecture, and business teams.

Essential Skills & Experience

• Strong experience designing enterprise-scale AI and Machine Learning solutions.
• Experience with Generative AI, LLMs, Agentic AI frameworks, and RAG architectures.
• Expertise in cloud-native architecture, preferably Google Cloud Platform (GCP).
• Knowledge of MLOps, LLMOps, model deployment, monitoring, and lifecycle management.
• Experience with distributed systems, APIs, microservices, and event-driven architectures.
• Strong architecture modelling, design documentation, and governance experience.
• Understanding of Responsible AI, AI security, and regulatory considerations.
• Excellent stakeholder management and communication skills.

Preferred Technical Skills

• Google Cloud Platform (Vertex AI, BigQuery, GCS).
• Python and AI/ML ecosystems.
• LangGraph, LangChain, ADK, orchestration frameworks.
• Vector databases and Retrieval-Augmented Generation (RAG).
• Kubernetes, Docker, CI/CD, DevOps practices.
• Data architecture and data engineering concepts.
• Enterprise integration and API management.

Leadership Expectations

• Act as a recognised technical leader within the AI architecture community.
• Mentor Solution Architects, Engineers, and Data Scientists.
• Drive adoption of architecture standards and best practices.
• Promote innovation while maintaining strong governance and risk management.
• Influence strategic technology decisions through thought leadership.

Success Measures

• Delivery of scalable and secure AI solutions.
• Adoption of reusable architecture patterns.
• Improved time-to-market for AI products.
• Compliance with architecture, risk, and governance standards.

Positive business outcomes through AI-enabled capabilities