Feb 2025 – Present · 1 yr 1 mo

• Leading a 9-member team across backend, data, and applied AI to build large-scale personalisation systems that power recommendations, MarTech decisioning, and emerging agentic travel experiences.
• Own and scaled the Experience Engine for cross-sell and recommendations across high-traffic surfaces such as home, funnel, and post-booking journeys, serving hundreds of millions of requests with sub-100 ms P99 latency. Drive both the platform architecture and the business-facing decisioning capabilities.
• Led the team building an agentic AI Trip Planner that generates 1-click bookable itineraries under real-world cost, time, and distance constraints, combining orchestration and ranking to achieve 70%+ successful delivery.
• Led the orchestration brain for ContextOS — the execution layer for agentic workflows, responsible for agent planning, memory, execution state management, etc. Delivered the first production use case through an Audience Agent that enables marketing teams to create target audiences using natural language,
• Lead the engineering charter for MarTech and user decisioning platforms powering millions of personalised triggers per day, including retargeting, cross-sell, fare-drop alerts, and lifecycle engagement use cases.
• Own the org-wide Feature Store and real-time data APIs that serve personalisation use cases at more than billions of requests per day with sub-70 ms P99 latency, creating a common foundation for reusable features, online inference, and high-scale decisioning.
• Strong focus on technical depth and engineering rigor: careful translation of research ideas into production systems, deep ownership of distributed systems , technical and business metric monitoring, relevance/regression testing, data quality and production excellence.
• Stack: Scala, Java, Python, Redis, Aerospike, RocksDB, Spark, Kafka, S3, Delta, Avro, Docker, ReactJS.

Mar 2023 – Feb 2025 · 1 yr 11 mos

Apr 2021 – Mar 2023 · 1 yr 11 mos

Dec 2019 – Apr 2021 · 1 yr 4 mos