AI Strategist, Senior Manager

Role Summary

The Senior Manager, AI Builder is a hands-on client advisor and engagement lead responsible for converting business challenges into structured AI opportunities and implementation plans. The role conducts maturity and readiness assessments, facilitates discovery and use-case prioritisation, builds business cases, shapes PoCs and proposals, and manages day-to-day delivery. The Senior Manager works closely with senior AI Builders and multidisciplinary teams to create high-quality, reusable client assets and measurable outcomes.

Key Responsibilities

Discovery and analysis: Interview stakeholders, document business processes and pain points, analyse data and readiness, and identify suitable AI, GenAI and agentic use cases.
Use-case prioritisation and roadmap support: Evaluate value, feasibility, risk and dependencies; develop prioritisation models, phased roadmaps and adoption recommendations.
Business case development: Build benefit hypotheses, cost estimates, ROI models, KPI baselines and value-tracking plans with support from finance, delivery and industry specialists.
Solution and proposal development: Translate requirements into solution concepts, PoC scope, work plans, assumptions, risks and proposal content; coordinate inputs from architects, engineers, data specialists and partners.
Engagement delivery: Manage workplans, junior team members, client meetings, actions, quality and executive-ready outputs for consulting assignments and PoCs.
Responsible adoption: Incorporate governance, security, privacy, human oversight and change-management considerations into recommendations and delivery plans.
Market enablement: Research industry trends, create reusable use-case content and demos, support account pursuits, and share lessons across the APJ AI Builder community.

Key Performance Indicators

Quality and on-time completion of assessments, roadmaps, business cases, proposals and PoCs
Pipeline and bookings influenced through assigned pursuits and client engagements
Client stakeholder satisfaction and progression from discovery to funded next step
Reusable assets, insights and team upskilling contributions

Billability: 30%

Experience & Skills

Typically 8–12 years of experience in consulting, business analysis, product or programme management, technology strategy, data and AI, or digital transformation.
Experience leading workstreams or small teams and working directly with senior client stakeholders in discovery, advisory, solution or delivery settings.
Practical understanding of Generative AI, Agentic AI, LLMs, RAG, context engineering, Responsible AI, governance, enterprise data and cloud AI platforms.
Strong analytical skills in process assessment, use-case evaluation, roadmap development, benefits modelling and preparation of executive-ready materials.
Ability to coordinate across business, architecture, engineering, data, security and change teams and to manage ambiguity in fast-moving engagements.
Relevant industry or functional expertise and the ability to explain technical concepts in clear business language.

Bachelor’s degree or equivalent experience; relevant AI, cloud, data, agile, product or consulting credentials are advantageous