Key Responsibilities
1. Solutioning & Proposal Development
Partner with Senior SMEs and Practice Leads to design end-to-end Data & AI solutions for client pursuits — contributing to structure, content, and commercial framing.
Build client proposals, solution documents, and program structures that are well-organized, accurate, and ready to use without significant rework.
Translate client requirements into structured, outcome-oriented learning journeys — adoption, capability uplift, and measurable business outcomes, not just module lists.
Support customized offerings across Data Engineering, AI / ML, and GenAI and Agentic AI tracks; help assemble pursuits from existing accelerators rather than rebuilding from scratch.
2. Client Engagement Support
Participate in client discussions, discovery calls, and requirement-gathering sessions — capture context with the rigour that makes the next conversation sharper.
Convert business needs into solution frameworks and delivery models with guidance from Senior SMEs; document customer priorities so Practice and Sales can act on them.
Support pitch decks, case studies, and success stories — buyer-specific, visually clean, and aligned to how the customer thinks about their own problem.
Stay engaged through the proposal cycle and handoff to delivery; ensure no requirement gets lost between discovery and execution.
3. Content & Program Structuring
Assist in designing curriculum outlines, learning journeys, and hands-on lab structures that hold up against real-world enterprise contexts.
Work with internal and external SMEs to ensure content aligns with current industry trends, real use cases, and business outcomes — not generic technology overviews.
Maintain a library of reusable program structures, slide assets, and case study inserts; flag gaps in the existing content library proactively.
4. Research & Market Intelligence
Track trends across the AI / GenAI / LLM ecosystem and Data Engineering & Analytics — translate findings into usa
📌 Data AI and Practice (India)
🏢 NIIT
📍 India