Entrepreneur in Residence

15 years

0 Lacs

Posted:20 hours ago| Platform: Linkedin logo

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Work Mode

On-site

Job Type

Full Time

Job Description

Entrepreneur in Residence (EIR)-AI Platform & Business


This role is designed for a true builder—someone who thrives in ambiguity, bridges deep technology with commercial opportunity, and has the leadership maturity to operate a startup within a global enterprise.


strategy, product, engineering execution, go-to-market, customer adoption, P&L, and market expansion


Key Responsibilities

Vision, Strategy & Business Ownership

  • Define and own the long-term vision for an enterprise AI platform and solutions portfolio.
  • Develop a multi-year business strategy encompassing investment planning, market positioning, revenue models, and a clear scale roadmap.
  • Own P&L accountability, platform monetisation, growth outcomes, and investor-style business metrics.
  • Identify whitespace opportunities, new product lines, and sustainable differentiation in a rapidly evolving AI landscape.


Product & Platform Leadership

  • Lead the design and development of an enterprise-ready AI platform with a multi-use-case foundation, modular architecture, and built-in governance, observability, and security-by-design.
  • Own product roadmap definition, feature prioritisation, value articulation, and customer-backed solution frameworks.
  • Drive platform capabilities across generative AI, multi-model orchestration, LLMOps, vector stores, domain-specific AI accelerators, and API-first ecosystem design.
  • Ensure platforms are scalable, cost-efficient, measurable, and seamlessly integrable within complex global enterprise environments.


Engineering & Technical Execution

  • Build and lead high-trust engineering teams across product engineering, MLOps, data engineering, and platform reliability.
  • Accelerate execution across the full lifecycle: PoC → MVP → enterprise rollout → market-scale adoption.
  • Enforce strong standards around quality, security, responsible AI, compliance, and governance.
  • Champion a culture of experimentation while balancing enterprise-grade rigor and delivery discipline.


Go-to-Market, Sales & Ecosystem Growth

  • Own the go-to-market architecture, including ICP definition, pricing, packaging, commercial models, and partner strategies.
  • Hire, mentor, and scale sales teams, solution architects, customer success leaders, and forward deployment engineers (FDEs).
  • Build and convert enterprise pipelines, lead strategic customer engagements, and influence C-suite stakeholders to drive recurring revenue.
  • Establish and grow strategic alliances with hyperscalers, AI model providers, SaaS platforms, system integrators, and industry partners.


Leadership, Talent & Culture

  • Build a startup-within-the-enterprise culture that is bold, fast-moving, experimentation-driven, and learning-oriented.
  • Recruit, mentor, and develop product leaders, engineering managers, solution leaders, and GTM owners.
  • Drive strong alignment and execution velocity across Product, Sales, FDE, and Services organizations.
  • Lead by example—remaining hands-on when needed, from customer conversations and sprint reviews to investor-style strategy formulation.


Required Qualifications & Experience

  • 12–15 years of experience in senior product, engineering, or business leadership roles.
  • Demonstrated track record of launching and scaling technology businesses, preferably in

    AI/ML, platform software, or SaaS

    .
  • Strong understanding of

    LLMs, Generative AI, vector databases, RAG architectures, security, cloud platforms, and enterprise-grade system design

    .
  • Prior experience with

    P&L ownership, fundraising or board exposure

    , or high-growth incubation within startups or large organizations.
  • Ability to operate with high autonomy, make bold decisions, and lead multi-disciplinary teams at scale.
  • Strong technical education in

    Computer Science, AI/ML, or Software Engineering

    from

    IITs, IISc, or equivalent elite global institutions

    (e.g., MIT, Stanford, Berkeley, CMU).
  • Experience building and scaling businesses;

    ex-startup founders are strongly encouraged to apply

    .
  • Deep curiosity and passion for AI and its transformative impact on enterprise businesses.

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