Director of Forward Deployed Engineering

Company Overview TENEX is an AI-native, automation-first, built-for-scale Managed Detection and Response (MDR) provider. We combine cutting-edge AI with human expertise to deliver security operations that are better, faster, and more cost-effective than traditional approaches. We're a fast-growing startup backed by industry experts and top-tier investors led by Crosspoint Capital. Our team is mission-driven, customer-obsessed, and building something that matters — a new standard for how security operations should work. Culture is one of the most important things at TENEX.AI — explore our culture deck at culture.tenex.ai to witness how we embody our values every day. This role is perfect for those already in the Scottsdale, AZ, Sarasota, FL or Kansas City, MO metro area, or eager to join us. Immerse yourself in a high-performance environment built on integrity, innovation, and a relentless drive to protect our customers. About the Role TENEX.AI is the AI-native, human-led MDR provider. This Director owns the foundational delivery of our MDR service: how we build, deploy, manage, and integrate the platforms our service runs on: Google SecOps, Microsoft Sentinel, and the Tenex Platform. The mandate is time-to-protection and repeatable, high-quality multi-SIEM delivery at scale, standing platforms up cleanly, wiring in the customer's data and tooling, operationalizing detecti [... source excerpt omitted ...] closely with the teams that deliver advisory engagements and develop agentic use cases; deploying and integrating what they produce and relaying field context back to them. What You'll Do Own time-to-protection across our supported platforms — the speed and repeatability of standing up Google SecOps, Microsoft Sentinel, and the Tenex Platform in customer environments for example. Lead multi-SIEM engineering — build, deploy, and manage pipelines, parsers, detections, playbooks and other configuration across Google SecOps, Microsoft Sentinel, and the Tenex Platform. Own integrations — data-source onboarding, connector/API work, and normalization that wire the customer's envi [... source excerpt omitted ...] terns that get reused, not rebuilt. Own context engineering — the data mappings, entity resolution, tuning, and environment knowledge that make the platforms actually perform per customer. Own ongoing platform management — health, optimization, and lifecycle of deployed platforms across the book of business. Build the repeatable delivery machine — playbooks, intake, quality gates, and a capacity model that let the team scale against pipeline instead of heroics. Lead and scale the team — hire, coach, and develop the engineers responsible for platform implementation, content, and integration; manage capacity against the customer pipeline; own delivery quality, SLOs, and OKRs.