Note: The job is a remote job and is open to candidates in USA. DTEX is the leader in risk-adaptive security, unifying human, data, and AI risk through a behavioral intelligence platform. They are seeking a Director, Product Engineering to lead their AI POD, responsible for defining how enterprises understand, detect, and mitigate risk in the age of AI, while leading a cross-functional team to build capabilities addressing emerging risks from AI systems.
Responsibilities
- Own adoption, impact, and success of the AI pillar
- Define and drive the product strategy and roadmap aligned to DTEX’s platform vision
- Translate ambiguous, emerging problems into clear product direction and execution
- Operate a high-velocity POD model with engineering, product, design, and domain specialists
- Drive execution cadence, release planning, and milestone delivery
- Remove dependencies and ensure the team can ship quickly and predictably
- Define and evolve the AI architecture for the pillar (e.g., behavioral analytics, anomaly detection, LLM-driven reasoning, signal fusion)
- Drive decisions on build vs. leverage vs. partner across models, infrastructure, and data pipelines
- Ensure systems are production-grade—observable, explainable, and privacy-preserving
- Rapidly iterate from data → insight → model → product capability
- Partner with Sales, Customer Success, and Marketing to bring new capabilities to market
- Shape POVs, customer narratives, and early adoption strategies
- Incorporate real-world customer feedback into product direction without introducing churn
- Deliver solutions that are stable, scalable, and enterprise-ready
- Uphold strong engineering practices across reliability, performance, and deployment
- Track and improve delivery effectiveness (e.g., lead time, deployment frequency, iteration velocity)
Skills
- Proven experience leading cross-functional product and engineering teams to deliver high-impact outcomes
- Strong technical background with the ability to guide architecture-level decisions
- Experience building or deploying production AI/ML systems (e.g., behavioral models, anomaly detection, LLM-based systems, or data-driven platforms)
- Ability to operate in high-ambiguity, rapidly evolving technical domains
- Demonstrated use of AI to accelerate both product capabilities and development workflows
- Strong communication and executive alignment skills
- Experience in one or more of: AI security or model risk
- Behavioral analytics / UEBA
- Data protection or modern DLP systems
- Familiarity with: LLM ecosystems and agentic architectures
- Signal processing and detection pipelines
- Enterprise SaaS product development at scale
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