Teams at Currence

Own the roadmap for a core data engine, prioritizing datasets, defining data structures and access, and ensuring product value reaches customers. Partner with engineers, analysts, commercial teams, and sales; prototype with messy datasets; manage data quality, metrics, user research, release planning, and stakeholder decisions. The role requires SQL fluency, familiarity with LLM or agent-based pipelines, and experience delivering technical or data-heavy products from user problem through launch.

Own customer renewals, onboarding, adoption, retention, account health, and engagement across a portfolio of subscription and research customers. Partner with Account Managers and analysts, connect customers to relevant research, communicate customer feedback internally, and build the company’s customer success playbook, health scoring, engagement cadence, and AI-assisted coverage model.

Build and operate AI backend systems, agentic workflows, RAG pipelines, evaluations, and LLM-powered data pipelines. Develop data-layer capabilities, monitoring, inspection interfaces, and production-grade software across Python, Dagster, PostgreSQL, Elasticsearch, and Iceberg. Collaborate with product, research, and commercial teams, own technical projects and PoCs, and balance security, quality, and delivery speed in a high-ownership startup environment.