• Lead the development of a multi-agent platform — a reusable foundation of AI agents, tools, orchestration logic, and shared infrastructure. • Collaborate closely with other teams (e.g., Data, QA, DevOps, Product) to ship AI features end-to-end — from dataset preparation to model integration, deployment, optimization, and monitoring. • Build and maintain automated AI pipelines using specialized frameworks or custom orchestrators. • Design robust logging, tracing, and metric systems for AI workloads; analyze performance using Elasticsearch, Prometheus, and Grafana. • Document architecture decisions, experiment results, and best practices in Notion. • Use deep GenAI expertise to evaluate trade-offs, propose high-impact solutions, simplify workflows, and maximize value for internal teams and external clients. • Share knowledge and architectural patterns with the team to strengthen internal GenAI expertise and maintain high engineering standards. • Provide the full lifecycle of GenAI features — design, development, deployment, monitoring, and long-term maintenance.