Responsibilities
- Define and manage the strategic direction of an internal AI platform, ensuring services are scalable, reliable, and simple to integrate for all internal teams, eliminating the need for external API dependencies.
- Collaborate closely with domain and product teams to identify AI integration opportunities that improve client-facing features through predictive modeling and personalized experiences.
- Partner with internal teams to apply AI capabilities toward increasing operational efficiency, including system scalability, fraud detection, and performance optimization.
- Lead the execution of key AI initiatives across the organization by synchronizing timelines and workflows among AI platform, domain, and mobile teams.
- Serve as the primary advocate for responsible AI, ensuring compliance with regulations, data privacy laws, and ethical standards across all model development and data usage.
- Oversee the end-to-end lifecycle of client-facing AI features, from planning and launch to post-release monitoring, coordinating across Product, Engineering, Data, Operations, and Compliance.
- Manage the agile development process for a cross-functional AI team, including backlog prioritization, sprint planning, and translating business objectives into technical user stories for data and ML specialists.
- Use data analytics, internal and external user needs, market developments, and insights from LLM outputs, trace logs, and agent performance to refine the AI platform's strategy and roadmap.
Team
Structure: cross-functional team of Data Scientists, AI Engineers and Software Engineers
