Director of Engineering (Data Platform)

Director of Engineering – Data Platform

About Vectra AI

Vectra AI is transforming cybersecurity through AI-driven threat detection and response.Our platform ingests and analyzes petabytes of customer telemetry, including network packets, logs, identity signals, and security events, to surface real-time insights, advanced detections, and autonomous security outcomes. The Data Platform organization sits at the heart of that mission, powering analytics, detections, machine learning, and next-generation AI capabilities.

The Opportunity

We're looking for a Director of Engineering to lead the teams that form the foundation of everything Vectra builds. You'll own the systems that ingest, process, store, and analyze petabytes of security telemetry daily, and you'll drive the platform forward to support modern AI workloads, autonomous security workflows, and next-generation analytics.

This role is first and foremost an organizational leadership role, but technical credibility is non-negotiable. You'll need to be architecturally fluent, able to engage deeply on system design, challenge assumptions, and identify risks before they become problems. You'll work closely with our platform architects on technical direction, but you're expected to bring your own point of view and push back when something doesn't hold up.

What You'll Do

People and Organizational Leadership

• Build, grow, and mentor high-performing engineering teams across multiple geographies.

• Develop engineering managers and senior technical leaders through coaching, sponsorship, and career investment.

• Foster an inclusive culture built on trust, ownership, and accountability, where distributed teams can do their best work.

• Create the conditions for strong execution: clear priorities, healthy team rhythms, and an environment where engineers can focus on meaningful work.

Cross-Functional Leadership

• Align priorities and investment decisions with Product, Security Research, AI, Infrastructure, and Customer teams.

• Communicate platform strategy, progress, risks, and trade-offs clearly to executive leadership.

• Partner with customer-facing teams to understand evolving data requirements and scaling challenges.

• Influence company-wide direction around data, AI, and platform capabilities.

Execution and Operational Excellence

• Lead delivery of large-scale platform initiatives, balancing innovation, reliability, and speed.

• Set engineering best practices across data processing, schema evolution, data quality, and service-level objectives.

• Own production operations, incident management, and continuous improvement.

• Ensure predictable delivery while keeping a clear line of sight to customer impact and long-term platform health.

Technical Strategy and Platform Direction

• Engage deeply on architecture decisions for scalable, reliable, and AI-ready infrastructure, able to ask hard questions, identify gaps, and pressure-test designs alongside platform architects.

• Champion a platform-first mindset with self-service APIs, strong developer tooling, observability, and documentation that accelerate Data Science, AI/ML, and product teams.

• Drive adoption of modern platform capabilities including feature stores, vector storage, and model serving infrastructure.

• Champion the use of AI to improve engineering productivity, software delivery, and incident response.

What You'll Bring

Required

• 10+ years of software engineering experience, including 5+ years leading engineering organizations.

• Proven track record building and operating large-scale data platforms in production.

• Deep expertise across large-scale data infrastructure: distributed systems, data ingestion pipelines, stream and batch processing, and storage systems at scale including object stores, columnar databases, and time-series systems.

• Champion the use of AI to improve engineering productivity, software delivery, and incident response.

• Experience with Databricks, including Spark-based processing and the Databricks platform ecosystem.

• Experience running ML or AI workloads in production, including platforms, feature stores, or inference infrastructure.

• Operational mindset: SRE principles, incident response, and a culture of reliability.

• Experience building or operating platforms that support LLM-based applications, including retrieval, embeddings, and model serving.

Preferred

• Background in cybersecurity, NDR, SIEM, XDR, observability, or related domains.

• Track record optimizing cloud costs and performance at scale on AWS, Azure, or GCP.

• Background in real-time detection systems or streaming analytics

What Success Looks Like

• A platform trusted and widely adopted by Data Science, AI, and engineering teams, known for reliability, self-service, and ease of use.

• Faster time-to-production for analytics, detections, and AI-powered applications.

• Reduced time from telemetry ingestion to model experimentation and deployment.

• High-performing teams with strong leadership pipelines and a culture people want to stay in.

• Industry-leading infrastructure supporting both advanced detections and autonomous security operations.

Why This Role Matters

Every detection, investigation, and AI-driven insight Vectra delivers runs on the platform you'll lead. You'll shape the organizational and technical direction of a platform that protects organizations worldwide from some of the most sophisticated threats in existence, and you'll build and develop the teams that make it possible.