VP of AI, Enterprise Optimization & Automation

International Data Group, Inc.

1d•$320,000 - $437,000•Remote

About The Position

IDC is building the next generation of AI-powered intelligence platforms that transform how technology decisions get made. Our platform re-imagines the way decision-makers discover and interact with trusted research and data, and is foundational to IDC's future. We are bringing the same AI-first mindset to our own operations. We are looking for a VP of AI, Enterprise Optimization & Automation to lead a new internal function dedicated to modernizing how IDC works. You will build and lead a team of forward-deployed engineers and technical specialists who embed with internal teams — finance, data creation, HR, sales operations, and others — to identify high-leverage automation opportunities, build working prototypes using AI and LLM-powered tooling, deploy what works, and move on to the next problem. This is not a traditional IT or process improvement role. You will run a fast-moving technical team that treats internal operations the way a product team treats a product: discover pain points through direct observation, prototype solutions rapidly, measure impact, and iterate. Your team will rotate across the company, parachuting into functions that need help, delivering working automation, then handing off and redeploying. You will set the technical strategy, prioritize where your team deploys, build relationships with business leaders across IDC, and maintain a portfolio of active and completed engagements. You will interact with and report to senior leadership on an ongoing basis.

Requirements

12+ years of experience in engineering, technical operations, or technology consulting, with at least 5 years in a leadership role directing technical teams
Demonstrated track record of deploying AI/ML or LLM-powered solutions that automated or materially improved real business processes — not just proofs of concept
Experience running an embedded or forward-deployed team model, consulting engagement model, or internal services function where your team rotated across different business areas
Strong hands-on technical foundation — you have built systems yourself and can evaluate your team's architectural decisions, even if you are no longer writing production code daily
Ability to build trust and working relationships with non-technical business leaders across functions (finance, HR, data operations, sales) and translate their problems into technical solutions
Experience prioritizing a portfolio of opportunities with varying complexity, risk, and payoff, and making hard sequencing decisions
Comfort operating with significant autonomy — you will define your own team's roadmap based on where you see the highest-impact opportunities

Nice To Haves

Direct experience building with LLMs, AI agents, or AI-assisted workflow tools (not just overseeing teams that do)
Background in management consulting, internal consulting, or a forward-deployed engineering function at a technology company
Experience with enterprise process automation across multiple domains (finance, HR, data operations, content production)
Familiarity with the operational realities of a research and advisory firm or professional services organization
Track record of standing up a new function or team from scratch within an established organization
Experience establishing lightweight governance frameworks for AI tool adoption

Responsibilities

Build, lead, and grow a team of forward-deployed engineers and technical specialists (starting at 3-5, scaling as impact proves out)
Identify, prioritize, and sequence automation opportunities across IDC's internal functions by engaging directly with business leaders and their teams
Set the technical strategy for internal automation, with AI and LLM-powered solutions as the primary approach
Run an engagement model where your team embeds with internal groups, builds rapid prototypes, validates with users, and deploys production solutions
Manage a portfolio of active engagements, balancing quick wins with longer-horizon transformation projects
Define handoff and sustainability standards so that deployed automations remain operational after your team moves on
Build and maintain internal credibility by delivering measurable results — reduced cycle times, eliminated manual steps, improved accuracy, freed capacity
Establish governance around AI-powered internal tools, including data handling, access controls, and appropriate use policies
Report on portfolio progress, impact metrics, and roadmap to senior leadership