Company overview:

Blue Orange Digital helps organizations unlock measurable business value with modern analytics and AI. We are entering a focused growth phase serving Private Equity (PE) firms and their portfolio companies, delivering AI solutions that drive EBITDA uplift, revenue acceleration, and operational efficiency across hold periods.

Role Summary

The Vice President of AI is a senior, client‑facing leader who combines executive‑level consulting with hands‑on AI execution credibility. You will:

• Shape diligence findings, author 100‑day AI plans, and govern solution strategy.
  
  

• Partner with AEs and leadership to originate and shape opportunities, lead discovery and scoping, and craft compelling proposals.
  
  

• Direct the build of secure, scalable AI products (e.g., LLM copilots, retrieval/RAG systems, intelligent automation, forecasting) that deliver quantified value.
  
  

Center of gravity: Executive advisor who owns solution governance and business outcomes. Day‑to‑day delivery ownership sits with an Engagement Lead; you set the vision, acceptance criteria, and sign‑off.

Reports to: CEO/CTO

Leads: Will build a small AI strategy pod (2–5) with dotted‑line influence over Solution Architects & Principal Engineers; does not directly manage delivery squads.

Location: NYC.

Travel: 25–40% to PE offices, portfolio sites, and industry events.

Work Authorization: Candidates must be authorized to work in the US.

Compensation: Competitive base + variable with upside tied to influenced revenue and firm performance (indicative OTE range $220k–$320k, adjusted for market/experience).

Key Responsibilities

1) AI Consulting for the PE Lifecycle

• Deal flow / Diligence (2–3 weeks): Run rapid AI opportunity scans, assess tech/data readiness and risks (security, privacy, IP, model risk), and produce a value hypothesis with sizing.
  
  

• 100‑Day Plan: Prioritize 2–3 high‑impact bets with quantified ROI, staffing/budget, architecture approach, and clear acceptance criteria.
  
  

• Hold Period Scaling: Build reusable components and playbooks; implement shared services and enable cross‑portco rollout for repeatable gains.
  
  

• Exit Readiness: Assemble value evidence (before/after KPIs), maturity roadmaps, and buyer‑facing narratives that crystallize AI‑driven enterprise value.
  
  

2) Solution Leadership & Governance

• Own solution vision and reference architectures for LLM/RAG, predictive & prescriptive models, and intelligent automation.
  
  

• Translate strategy into data/feature readiness, MLOps/LLMOps pipelines, and measurable success criteria (KPIs, SLAs, cost of serve/TCO).
  
  

• Establish and enforce AI risk controls, including evaluation harnesses, bias/safety guardrails, human-in-the-loop approvals, PII handling, auditability, observability, and drift management.
  
  

• Guide delivery from prototype to production; approve go‑live against security, reliability, and ROI thresholds.
  
  

3) Go‑to‑Market & Proposals

• Own win themes and solution narratives in RFPs and pitches; partner with Sales Ops on assumptions, pricing guardrails, risks, and acceptance criteria.
  
  

• Develop diagnostics, ROI models, and diligence checklists that accelerate pursuit cycles and improve win rates.
  
  

• Represent Blue Orange at PE and AI industry events; deliver talks/demos that open doors and build trust.
  
  

4) Thought Leadership & Practice Building

• Publish white papers, teardown analyses, and LinkedIn POVs that position us as the leader in AI for PE value creation.
  
  

• Mentor architects/engineers/consultants in consulting fundamentals (facilitation, scoping under ambiguity, stakeholder management).
  
  

• Shape hiring, training, and strategic partnerships across cloud, data, and AI ecosystems.
  

Requirements

Must‑Haves

• Led 2+ production AI programs with quantified EBITDA/revenue/cost impact and documented before/after metrics.
  
  

• Demonstrated PE/Portco advisory or value‑creation experience.
  
  

• Strong consulting experience: Executive advisory, facilitation, value cases/proposals, stakeholder alignment, and driving adoption from pilot to scale.

• Knowledge in LLMs/GenAI & RAG, including evaluation strategies, LLMOps/MLOps, governance, and safety.
  
  

• Executive consulting: run discovery, craft AI roadmaps and investment cases, and present to C‑suite/boards.
  
  

• Working fluency in Python and one major cloud (AWS/Azure/GCP); able to review/guide architectures and cost models.
  

Nice‑to‑Haves

• Knowledge of PE value‑creation frameworks (synergy models, carve‑outs/roll‑ups, 100‑day execution).
  
  

• Certifications (cloud AI/ML; Databricks/Snowflake) or advanced degree (MS/PhD/MBA).
  
  

• Sector experience in Industrial/Manufacturing, B2B Services, Healthcare, CPG/Retail, or other common PE areas.
  
  

• Public thought leadership and conference speaking track record.
  

Success Metrics (12 Months)

• $‑Impact: Documented EBITDA/revenue/cost improvements within 6–12 months post‑launch, tied to baselines and acceptance criteria.
  
  

• Speed to Value: Discovery → pilot in weeks; production in months with adoption plans.
  
  

• Scalability: Playbooks/components reused across multiple portcos.
  

GTM: Net‑new opportunities sourced via conferences/content and improved proposal win rates on pursuits you lead.