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
Job description provided by Cognizant Technology Solutions.
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