Director - Technology Development

Job Title : Director — Technology Development (Personalization)

Location : Bengaluru

Experience : 15+ Years

Function : Data Platform & Personalization

Why This Role

Reimagine travel personalization at platform scale across Flights, Hotels, Holidays, Trains, and Activities.

Own end-to-end personalization charter : engineering, data science, MLOps, and experimentation.

Collaborate with ContextOS, Myra, and Experience Hub under the “One Brain, Many Adapters” vision.

What You’ll Own

Strategy & Roadmap : Drive 12–18 months personalization roadmap aligned to KPIs (growth, conversion, retention, experience).

Platforms, Not Projects : Build reusable ranking / reco / decisioning platforms (feature / embedding store, real-time signals, policy / constraints, evaluation).

ML in Production : Lead model lifecycle (user modeling, content understanding, candidate generation, re-ranking, optimization, bandits / RL) with clear SLOs.

Experimentation & Causality : Scale A / B and bandit experimentation; ensure robust guardrails and uplift measurement.

Privacy-First Personalization : Embed consent, PII handling, and privacy-by-design in data contracts; ensure regulatory compliance.

Agentic & Real-Time Experiences : Integrate with ContextOS and Myra for explainable, grounded, actionable recommendations across channels.

People & Org : Lead a 25–40 members team across Backend / Platform engineers, MLEs, DS / Applied Scientists, and Program; hire, coach, and build succession.

Partnering & Influence : Collaborate with Product, Design, Marketing, Supply, Finance, and Legal; manage vendors / partners.

Observability & Evals : Establish evaluation frameworks and operational excellence (SRE, On-call, RCA).

Cost & Reliability : Own budgets, infra choices, and efficiency (GPU / CPU mix, caching, quantization, distillation).

What You’ve Done

15+ years in consumer tech / platforms with 7+ years leading cross-functional Eng + DS / MLE teams.

Delivered production ML (recommendations / ranking / search / ads / feeds) for millions of users with measurable uplift and strong SLOs.

Built / owned feature & embedding stores, online feature serving, streaming pipelines, and A / B platforms.

Deep hands-on expertise in large-scale backend (Java / Scala / Go) or applied ML (Python, PyTorch / TensorFlow) with architectural leadership.

Experience with real-time systems (Kafka / PubSub, Flink / Spark Streaming), datastores (Redis, Cassandra / DynamoDB, Elasticsearch), MLOps (MLflow / Kube / Triton / Ray), and cloud (AWS / Azure / GCP).

Proven implementation of privacy-by-design, data contracts, and governance in production pipelines.

Strong product sense and storytelling; ability to align executives and mentor senior ICs and managers.

Nice to Have

Experience with multi-objective optimization, constrained ranking, or contextual bandits / RL.

Familiarity with knowledge graphs / ontologies, retrieval / RAG, agentic workflows, LangGraph / LangChain, and LLM / agent evaluation frameworks.

Experience in Indian consumer internet scale, marketplaces, or travel.