Own Technical Direction: Simplify, modularize, and future-proof a multi-platform system growing in complexity, spanning VR/PC/Web simulation, web authoring tools, and analytics infrastructure.
Define technical standards and architecture that raise the engineering ceiling for the entire team.
Shape AI Strategy in Practical Ways: Deliver AI-generated scenarios, adaptive learning systems, and AI-assisted development workflows.
Focus on turning AI into shipped product value.
Bring Discipline to Engineering Execution: Improve estimation accuracy, delivery predictability, and development velocity.
Establish scalable engineering patterns and a culture of quality and accountability.
Build for Scale Before It Breaks: Lead improvements in system reliability, uptime, observability, and performance as the company moves toward its next level of customer growth.
Turn Data Into a Core Product Capability: Drive analytics architecture to enable measurement of learner performance, simulation effectiveness, and product usage.
Help establish Lumeto as a data-driven platform.
Support Product Expansion: Ensure tight integration between simulation, competencies, and learning workflows.
Enable rapid iteration using modern AI development methodologies.

Proven track record building and operating scalable, cloud-native distributed systems in production at significant scale
real traffic, real orchestration, real failure modes.
Deep backend expertise across APIs, services, and the data layer, with the ability to be genuinely hands-on and write production-quality code, not only review it.
Strong infrastructure and orchestration maturity: Kubernetes at scale, CI/CD, infrastructure-as-code, observability, and cost-aware scaling.
Platform security as a default
authentication, secrets management, and network/data security designed from the start.
Modern web platform architecture, including real-time and streaming systems where relevant.
Deep Microsoft Azure experience, including sound judgment on managed-service-versus-build tradeoffs at scale.
Recent, hands-on experience building agentic and LLM-powered systems in production, including tool-calling, orchestration, evaluation, and the infrastructure to serve them reliably.
Strong understanding of the latency, cost, and reliability tradeoffs of model-backed systems at scale.
Sets technical direction, standards, and architecture; raises the engineering bar and mentors others to multiply impact.
Excellent communicator who can translate complex technical tradeoffs for non-technical stakeholders and align a team.
Genuine fluency working with data
instrumentation, metrics, and data-driven decision-making.

Technical Director

Key skills