VP of Products & Platform

Lead the MetaDefender platform as VP, owning technical vision for File Security Core, enterprise shared services, and AI-first/agentic capabilities. Drive category leadership, voluntary internal adoption, and P&L ownership in complex on-prem/cloud environments. Requires 15+ years platform leadership with deep AI, security, and enterprise deployment expertise.

About the job

MetaDefender Core — Product Strategy & Technical Direction

Own the technical vision for Core's evolution: modular multi-engine orchestration, processing throughput, format coverage, and API extensibility. Frame Core as the engine of File Security, not a scanner. Articulate at the platform level why protecting the complex enterprise file ecosystem (ingest, transfer, storage, collaboration, supply chain) requires layered, defense-in-depth file analysis, and why single-engine antivirus is structurally insufficient. Drive strategy to serve new file modalities, archives, encrypted containers, firmware, ML/AI model files as the attack surface expands. Ensure Core's architecture enables adjacent products rather than constraining them. Shape the growth trajectory with a path toward full P&L ownership as the role and platform mature.

Enterprise Shared Services — The Foundational Platform Layer

Own the unified platform every mature MetaDefender product adopts for a consistent, enterprise-grade experience. Shared Services spans cross-cutting capabilities: installation & deployment (online, offline/air-gapped, headless, automated), identity & access (SSO, RBAC, SAML/OIDC, federation), configuration & policy, observability, reporting & audit, HA/DR, zero-downtime scale, and shared UI components. Own the strategy, developer experience, and adoption outcome. Success is measured in voluntary adoption by peer teams.

AI-First Platform & Agentic Operations

Make agentic capability a native primitive of the platform — exposed to product teams as a service. Embed AI across operational surface: triage, configuration, deployment, observability, and customer time-to-value. Use AI to drive organizational change — accelerate engineering velocity, internal adoption, documentation, and decision speed. Model what an AI-first product org looks like. Define where human-in-the-loop is mandatory, design for AI failure modes, and prevent "AI theater".

Category & Business Leadership

Treat the platform as a business: own the narrative, positioning, and P&L. Define and lead the File Security category — language, reference architectures, buyer education, and competitive framing. Translate platform capability into enterprise buyer value and pricing leverage.

Enterprise Deployment & Infrastructure Expertise

Deep fluency required in:

On-Premises: Internet-connected and fully air-gapped, across Windows and Linux.
Cloud & IaaS: AWS, Azure, GCP — marketplace offerings, reference architectures, cloud-native integrations.
Kubernetes & Containers: Helm, operators, cloud-agnostic deployment patterns.
Hybrid & Edge: Centralized management with distributed processing.

First 12 Months

Months 1–3: Audit Shared Services adoption, Core architecture, deployment tooling, AI surface. Deliver prioritized platform roadmap and File Security category thesis.
Months 3–6: Establish platform team as internal product organization. Build relationships with product PMs and engineering leads. Ship quick wins including AI-driven ones.
Months 6–12: Drive measurable Shared Services adoption. Modernize Core for next-generation scale. Establish deployment patterns and agentic workflows that reduce customer time-to-value.

You will directly collaborate with 2 dedicated engineering teams (40+ headcount) while influencing platform adoption across 12+ peer engineering teams globally.

Requirements

15+ years in platform engineering, developer platforms, or infrastructure product management, with 5+ years in senior leadership owning platform strategy.
AI-first product leadership: demonstrated use of AI/agentic systems as product surface and operating model — including using AI to drive organizational change, velocity, and adoption. Working fluency in LLM evaluation, agentic design, human-in-the-loop, and AI failure modes.
Customer-deployed software depth (not pure SaaS): understanding of on-prem upgrades, air-gapped installs, and enterprise change management.
Architectural fluency across Kubernetes, containerization, IaaS (AWS/Azure/GCP), and traditional on-prem. Able to evaluate trade-offs and challenge engineering decisions.
File Security depth beyond antivirus: understanding of layered discipline (CDR, multiscanning, vulnerability and dynamic analysis, DLP, supply-chain/SBOM) and ability to articulate strategy and platform architecture.
Earned-adoption track record: internal platforms that other teams chose to adopt.