Vice President of Business Operations & Analytics

Responsibilities:

AI/LLM Strategy, Adoption & Performance
 
• Define and execute Comply’s enterprise AI roadmap—prioritize use cases, build-vs-buy decisions, and establish measurable ROI targets.
• Evaluate and experiment with frontier models (Claude, GPT-4o/o3, Gemini) and emerging architectures. Benchmark performance, understand model-family tradeoffs, and make informed adopt/switch/wait decisions. Keeping pace with this space is core to the role.
• Integrate LLMs into workflows: regulatory document analysis, compliance automation, predictive analytics, and intelligent search across structured and unstructured data.
• Design role-based AI adoption—match tools to personas across engineering, compliance, support, commercial, and finance. Evaluate options (code-assist, copilots, agent frameworks, embedded analytics) and drive adoption through fit, not mandate.
• Tie AI to productivity metrics by function: R&D velocity (code generation, Pull Request (PR) throughput, bug resolution via Claude Code, GitHub Copilot, Cursor); support (ticket deflection, first-response time, resolution rate); compliance ops (document review cycle time, regulatory change turnaround); Sales/RevOps (proposal speed, CRM data quality, pipeline analytics). Baseline, optimize, and report ROI.
• Architect AI for regulated financial services—auditability, data lineage, Personally Identifiable Information (PII) protection, model explainability. Partner with CISO on AI-specific security and compliance controls.
• Evaluate and operationalize AI tooling (LLM APIs, Retrieval-Augmented Generation (RAG) frameworks, vector databases, agent architectures, Model Context Protocol (MCP) integrations) with a clear build-vs-buy lens.
• Establish AI governance—data classification, access controls, model risk management, regulatory alignment (SOC 2, GDPR). Build organizational AI capability to sustain transformation beyond initial wins.

Data, Analytics & Business Intelligence

Lead analytics and BI strategy—reporting frameworks, executive dashboards, and operational metrics across revenue, product, finance, and client operations.

Establish data governance, KPI standards, and data quality practices. Own the single source of truth.

Oversee data engineering and the company’s data platform. Partner with Product and Engineering to surface regulatory data insights that inform roadmap and client value.

Enterprise Applications & Architecture

Own the systems roadmap across CRM, CPQ, RevOps, ERP, billing, contracting, and HR architecture decisions, integration strategy, and system retirement planning.

Drive interoperability and data consistency across GTM and finance. Eliminate manual handoffs and reconciliation gaps.

Technical counterparty to business application owners. Lead vendor evaluation, contract negotiation, and spend optimization.

IT Operations & Service Desk

Oversee corporate IT—end-user systems, infrastructure, security, and support. Define SLAs, escalation paths, performance metrics, vendor relationships, budgeting, and business continuity.

Partner with Security and Engineering leadership to maintain strong IT governance and operational resilience.

Skills & Qualifications:

• 12+ years in business operations, data/analytics, or enterprise systems; 5+ years leading cross-functional teams across data, applications, and IT.
• Hands-on experience designing and operating enterprise SaaS ecosystems—deep Salesforce and NetSuite expertise, not just oversight.
• Production AI/LLM experience: you’ve shipped AI-powered capabilities involving LLM integration, RAG, or AI-enabled automation. You can articulate frontier model tradeoffs and know when to use which one.
• Experience driving AI/LLM adoption at organizational scale—role-based tooling strategies, change management, and measurable productivity outcomes.
• AI governance and responsible AI practices in regulated or compliance-sensitive contexts.
• Financial services, Regulatory Technology (RegTech), or regulated industry experience where auditability and compliance are operating constraints.
• Executive partnership—translating business priorities into technology and data capabilities at the CEO/board level.
• Strong executive communication. You can present architecture decisions to the board and migration plans to a sales team.
• Based in DC metro; onsite in Arlington, VA.
Preferred Qualifications
• Advanced degree (MS, MBA) or certifications (Salesforce, NetSuite, ITIL, PMP, CISSP).
• Hands-on with frontier model ecosystems—Claude, GPT-4o/o3, Gemini—plus agentic workflows, MCP integrations, and API-based AI services in corporate environments.
• Instrumenting AI productivity metrics: developer velocity from code-assist, support deflection from AI knowledge bases, cycle time reduction in document workflows.
• Scaling data platforms and analytics teams through organic growth and M&A.
• Enterprise architecture or complex systems integration across GTM and finance stacks.
• Has stood up an AI Center of Excellence or equivalent organizational capability.