Growth Manager - Product Sales
Prodapt
- Location
- Chennai - Guindy, India
- Work model
- On-Site
- Level
- Mid
- Posted
- 3h ago
About this role
Overview
We are looking for a technical sales engineer who can own the full arc of a complex enterprise AI sale: explaining an AI platform to audiences ranging from C-suite executives to hands-on architects, running live product demonstrations, building industry specific use cases and business cases with customer success teams, and shaping go-to-market strategy for new verticals and regions. This role involves part solutions engineer, part strategist, part storyteller. Sitting at the intersection of product, sales, and customer success.
Responsibilities
Key Responsibilities Product demonstration and technical pitch - Deliver persona based product demos. Translate complex technical architecture into plain English narratives. Build sales enablement materials - Build primer documents, demo scripts, architecture explainer decks, and case studies that a prospect can absorb before or after a live session. Maintain a consistent narrative and vocabulary across all materials so prospects experience one coherent story regardless of who they talk to. Use case and business case development - Work with prospects / customers to identify their specific pain points & build use cases along with customer success teams. Go-to-market strategy and account targeting - Define and refine the ideal customer profile, screen and prioritize target accounts by fit and buying signals. Partner with sales leadership on territory and pipeline strategy. Competitive positioning Cross-functional coordination - Work closely with product management to stay current on capabilities and roadmap, and to ensure no capability is ever overstated to a prospect. Partner with marketing on collateral and messaging consistency, and with customer success on building use cases. Executive-level and technical audience communication - Comfortably shift register between a two minute executive one-pager and a whiteboard session on system internals with an engineering audience — always calibrating depth and language to who's in the room.
Requirements
A fast learner who can pick up new technical concepts quickly and get comfortable with unfamiliar subject matter. Genuine curiosity about AI and a willingness to keep learning as the technology and terminology evolve as this space moves fast, and the language you use with prospects today may need to shift in 3 months. Fluency in "AI language" — comfortable talking about concepts like MCP, LLMs, SLMs, and AI reasoning systems in a way that's accurate but still accessible to a non-technical audience. Working knowledge of the enterprise software and data landscape, and an understanding of how large organizations evaluate and adopt new technology. Adaptable across audiences and situations and also equally comfortable improvising through a technical question you weren't prepared for and adjusting a pitch on the fly when a conversation goes somewhere unexpected.Comfortable in figuring things out independently.