AI Engineer Team Lead - Innovation unit

Who are we?Skai (formerly Kenshoo) is a leading omnichannel marketing platform that leverages advanced AI and data-driven performance media to enable smarter decision-making, increased efficiency, and maximized ROI for businesses worldwide. Our platform helps manage approximately $10B in annual ad spend through partnerships with Google, Meta, Amazon, Microsoft, and others.Founded in 2006, Skai is a global company with around 650 employees. We operate in a hybrid work model that combines remote flexibility with in-office collaboration.What will you do?We are the Agents Studio group at Skai, operating as a high-speed development group within a global powerhouse. Following the initial launch of our flagship Agents Studio platform MVP, we are now scaling through our live Beta phase.In this role, you will serve as a GenAI-native technical lead, driving the rapid execution of our product strategy. You will connect live market feedback and customer needs directly to engineering delivery. Leading a dedicated pod of engineers, you will leverage advanced GenAI toolchains and translate real-world requirements into scalable, production-grade agentic solutions.Responsibilities:Drive Live Business Impact & Beta Launch: Rapidly engineer GenAI-assisted solutions, prototypes, and platform adjustments that unlock customer value and support Beta adoption.Command the Rapid Execution Pod: Lead a dynamic pod of 2-3 engineers drawn from core teams. Establish an AI-first development culture and agentic workflows to maximize team velocity and focus on high-impact business needs.Frontline & Client Alignment: Partner closely with Forward-Deployed Engineers (FDEs),Product teams, and clients to translate user feedback and market friction into solid architectural solutions.Dynamic Backlog & Roadmap Generation: Convert market signals and customer feedback into an actionable engineering backlog, taking end-to-end ownership from concept to production.Navigate the MVP-to-PMF Gap: Make pragmatic technical decisions daily, balancing fast GenAI prototyping with long-term, scalable core platform architecture.Agentic Workflows & AI Velocity: Build, scale, and maintain systems using GenAI coding toolchains and LLM frameworks, improving engineering output and setting standards for human-AI collaboration.Context Encoding & Technical Guardrails: Encode domain and organizational knowledge into scalable context layers, prompt pipelines, and fallback mechanisms to ensure system reliability and enterprise safety.Mentorship & GenAI Culture: Drive AI-native development practices across engineering teams, mentoring on practical AI adoption and fast-paced delivery.