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Director, Sales Lead — Google (Gemini Enterprise)

Artefact
New York, USA
Director
Onsite
Discovered 1 weeks ago

Full Job Posting

What you’ll do

  • Make Artefact top of mind with Google’s field: Map and work the account teams, customer engineers, partner managers and Gemini Enterprise specialists that matter. Run standing enablement (office hours, roadshows, account-team briefings, a forwardable one-page offer sheet) and show up where Google’s pipeline is made: QBRs, territory planning, field events. You are accountable for partner tier, partner NPS and the number of Google sellers who have put us in a deal.
  • Build the selling machine: Run co-sell with discipline (lead sharing, deal registration, joint account plans, a named pipeline review). Own Google’s funding instruments (AI value assessments, POC funding, practice-building support) so more of our pipeline arrives partner-financed. Build a repeatable path from first conversation to signed SOW, tracking partner-sourced pipeline, deals registered, conversion by stage and cycle time.
  • Sell: Generate pipeline with Google and through your own network. Run presales end to end and personally close, working 10-15 priority accounts that mix existing clients with whitespace Google brings. Advise CIOs, CDOs, CTOs and CEOs on where Gemini Enterprise fits their AI strategy, and turn delivered work into case studies and partner-validated proof points.
  • Build the offer: Package 3-5 flagship offers across Gemini Enterprise, Agent Gallery and ADK, Vertex AI and BigQuery, with clear entry points (assessment, pilot, scale), durations, staffing shapes and price anchors. Own reference architectures and the demo library, and write battlecards on when to lead with Google versus another stack.
  • Build the team: Recruit a small dedicated core plus experts from the shared pool, own the certification plan, run an internal community for the stack, and keep the practice profitable, not just busy.
  • Be visibly expert: Use AI tools daily, prototype with agentic coding tools, and contribute co-branded thought leadership with Google Cloud.
  • What success looks like in 12-18 months
  • Google’s Americas field calls us first, and named account teams have put us in live deals.
  • The co-sell machine, with registration, joint pipeline reviews and packaged, priced offers, works when you aren’t in the room.
  • A meaningful share of our pipeline is partner-financed.
  • Our AI-native partner status grows into deeper formal standing with Google, backed by a certified bench.
  • The book moves from project-by-project work to a repeatable Gemini Enterprise motion, with new logos and a dedicated core team.
  • What we are looking for
  • 8-10 years in consulting, technology or media, with a track record of winning work and building a book of business
  • Proven partner-sourced revenue through a hyperscaler or software alliance, and the ability to say what share of your number it was
  • Experience co-selling with Google sellers and customer engineers, plus Partner Advantage mechanics (badges, specializations, funding, deal registration)
  • C-level advisory experience on data, digital or AI transformation
  • Enough Google stack fluency (Gemini Enterprise, Agent Gallery, ADK, Vertex AI, BigQuery) to shape a solution with a customer engineer and advise a CIO on platform selection
  • Hands-on AI builder, comfortable in the terminal with agentic tools (Gemini CLI, Claude Code, Codex)
  • Experience leading and developing consulting teams, including recruiting and certification
  • Executive presence, sharp storytelling, and comfort with ambiguity: the book exists, the machine around it doesn’t
  • Preferred
  • Existing relationships inside Google Cloud’s partner, field sales or Gemini Enterprise teams
  • Alliance program experience (tiering, certification, co-sell, deal registration)
  • Vertical expertise in CPG, retail, luxury, financial services, healthcare or telecom
  • Experience taking clients from AI experimentation to scaled, governed adoption
  • Familiarity with RAG, semantic layers, knowledge bases and MCP

Qualifications

  • Familiarity with RAG, semantic layers, knowledge bases and MCP

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