AI Lead

Job Role

Lead AI for a LatentView entity, combining senior client advisory with deep technical leadership. Turn business priorities into viable AI engagements, from opportunity shaping and proposals through experimentation, production and measurable client value.

Partner with account leaders, the AI CoE and technology partners to grow engagements, teams and offerings. Match predictive or generative AI and automation to client needs.

What you will own

• Lead C-suite and senior business and technology conversations. Discover priorities, challenge assumptions constructively, and communicate AI value, feasibility and trade-offs.
• Qualify opportunities across the client portfolio. Connect workflows, data readiness and economics to the entity's AI roadmap, investment priorities and an agreed next step.
• Own implementable AI architectures across data, models, applications and enterprise integration. Evaluate foundation models, RAG/vector search and agentic workflows; review critical implementation choices and balance quality, security, latency, cost and resilience.
• Lead proposals and pursuits with account and delivery teams. Define solutions, scope, estimates, dependencies and acceptance criteria; balance competitive positioning, delivery feasibility and margin.
• Direct focused PoCs and pilots with agreed success measures and stop, adapt or scale decisions. Guide the transition to funded production, operational ownership, adoption and measured client outcomes.
• Establish AI governance with client and specialist teams: privacy, security, bias, IP protection, evaluation, change approvals and accountable risk ownership. Embed these controls throughout delivery.
• Build multidisciplinary AI teams and technical leaders. Set hiring priorities, strengthen engineering reviews and learning, and balance capability building with client delivery.
• Develop repeatable offerings and reusable assets with the AI CoE and partners. Build technical case studies; evaluate emerging technologies for differentiation and adoption.

Required skills

Hands-on experience with LLMs, RAG, vector databases and agentic workflows.