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
