You will own the end-to-end execution of product and feature launches while driving adoption and retention of programmatic and analytics products. Additionally, you will serve as the voice of the customer and create sales enablement materials to support the go-to-market strategy.
The role involves a 50/50 split between developing AI-driven features using Python on GCP and maintaining core platform services with Java and Spring Boot. You will be responsible for shipping LLM-backed products to production and driving AI-assisted development practices across the team.
You will own the lifecycle of data platform infrastructure, including architecture, deployment, capacity planning, and incident response. You will also focus on operational automation to reduce manual work and improve system reliability.
Collaborate with leadership to develop product vision and design optimized user journeys for B2B SaaS experiences. Lead user research and own UX features end-to-end, from requirement definition to delivery and KPI analysis.
The role focuses on modeling client growth to manage infrastructure capacity and optimizing cloud/AI usage costs. It involves monitoring query performance across various platforms and owning product analytics reporting to identify growth bottlenecks and waste.
The Site Reliability Engineer will own service health, incident response, and infrastructure monitoring for GCP-based APIs and data services. They will also manage cloud cost visibility and collaborate with engineering teams to ensure operational excellence and security.
