Director of Engineering Agentic AI

We are seeking an experienced Director of Engineering - Agentic AI Platforms to lead the architecture, strategy, and execution of next-generation enterprise AI platforms powered by agentic AI, generative AI, LLMs, autonomous workflows, and intelligent orchestration systems. This is a senior engineering leadership role requiring deep expertise in building scalable AI platforms from scratch, driving AI-first platform transformation, and leading large cross-functional engineering organisations.

The ideal candidate should have extensive experience designing and scaling enterprise-grade AI platforms involving agentic AI systems, multi-agent orchestration, LLM-powered workflows, RAG architectures, AI copilots, intelligent automation systems, AI infrastructure and orchestration frameworks. The candidate will work closely with Product, AI/ML, Data Science, Platform Engineering, and Executive Leadership teams to build scalable AI-driven enterprise ecosystems.

The candidate will have responsibilities across the following functions:

Engineering Leadership:

• Lead and scale large engineering teams focused on enterprise AI and agentic AI platform development.
• Define and drive engineering strategy, platform architecture, execution roadmaps, and operational excellence.
• Mentor engineering managers, architects, and principal engineers across distributed teams.
• Establish engineering best practices, platform governance, reliability standards, and scalable delivery frameworks.

Agentic AI Platform Development:

• Architect and build enterprise-scale Agentic AI platforms from scratch.
• Design scalable AI ecosystems supporting the following: autonomous AI agents, multi-agent orchestration systems, AI copilots and enterprise assistants, intelligent workflow automation, AI reasoning and decision systems, and context-aware enterprise AI applications.
• Drive platform capabilities for agent orchestration, memory management, tool integrations, prompt orchestration, workflow planning and execution, and AI observability and evaluation.
• Build reusable enterprise AI platform capabilities enabling rapid AI product development across business functions.

AI / GenAI Technical Expertise:

• Strong understanding of large language models (LLMs), generative AI ecosystems, RAG architectures, agentic AI frameworks, multi-agent systems, vector databases, AI orchestration frameworks, AI evaluation and observability frameworks, and enterprise AI governance and security.
• Collaborate closely with AI/ML, data science, and platform teams on AI infrastructure, scalability, reliability, and deployment strategies.
• Drive adoption of modern AI frameworks and enterprise AI best practices.

Platform Architecture and Scalability:

• Design scalable, cloud-native, high-performance AI platform architectures.
• Drive integration of enterprise APIs, data platforms, workflow systems, and AI services.
• Ensure platform scalability, security, fault tolerance, reliability, and operational readiness.
• Lead modernisation initiatives for enterprise AI infrastructure and distributed systems.

Stakeholder and Business Leadership:

• Partner with executive leadership to define AI platform vision, enterprise adoption strategies, and transformation roadmaps.
• Align AI platform investments with business goals and enterprise priorities.
• Drive cross-functional collaboration across Product, Engineering, AI/ML, Security, Data, and Operations teams.
• Define KPIs, platform success metrics, governance frameworks, and operational maturity models.

Requirements:

• 15+ years of experience in software engineering/platform engineering/distributed systems engineering.
• Strong leadership experience managing large engineering organisations and enterprise-scale technical platforms.
• Proven experience building AI or agentic AI platforms from scratch.
• Deep expertise in: Agentic AI systems, LLM-powered applications, distributed systems, Cloud-native architectures, Enterprise AI platforms, intelligent automation systems.
• Strong experience collaborating with AI/ML, Product, Data Science, and Architecture teams.
• Excellent stakeholder management, strategic thinking, and executive communication skills.