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AI Product Expert - Mahindra.AI

Kandivali Plant (AD), Kandivali Plant (AD), INPosted 3 days ago
onsite

Job Description

Responsibilities & Key Deliverables

Role Purpose

Lead the end-to-end strategy, build and scaling of AI-led products across Mahindra businesses—driving measurable business impact through data, AI, and platform-led solutions.

 

Key Responsibilities

 

1. Product Strategy & Vision

 

  • Define and own the AI product roadmap aligned to Mahindra group priorities (Auto, Farm, Financial Services, etc.)
  • Identify high-impact AI use cases (revenue growth, cost optimisation, customer experience)
  • Build long-term product vision with scalable, platform-led thinking

 

2. Product Development & Execution

 

  • Drive end-to-end product lifecycle: ideation → MVP → scale
  • Work closely with Data Science, Engineering, and Business teams to deliver AI-first products
  • Translate business problems into product requirements and technical solutions

 

3. Business Impact & Adoption

 

  • Own product adoption, ROI, and commercialisation of AI solutions
  • Partner with business leaders to embed AI into core workflows
  • Track KPIs: usage, impact, revenue/cost impact, model performance

 

4. Stakeholder Leadership

 

  • Influence senior stakeholders (CXOs, Business Heads) on AI-first transformation
  • Act as a bridge between business, tech, and analytics teams
  • Drive governance, prioritisation, and decision-making forums

 

Experience

  • 10–15 years of experience in Product Management / Strategy / Consulting
  • Strong experience in building/scaling digital or data/AI products
  • Exposure to platforms, ecosystems, or enterprise transformation is preferred

Industry Preferred

Qualifications

  • MBA from Tier 1 institute
  • Engineering / Analytics / STEM background preferred

General Requirements

Core Competencies

  • Strong product thinking with business impact orientation
  • Ability to work across ambiguity and drive 0→1 builds
  • AI/Data understanding (pro level user of LLMs, use case applicability, usage of AI agents to accelerate impact/product builds)
  • Executive stakeholder management (CXO level)
  • Structured problem solving (consulting-style thinking preferred)

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