Jobs at Lusha

Own full sales cycle for mid-market and enterprise customers: prospect, map stakeholders, apply MEDDPICC, negotiate, and close deals. Leverage GenAI and AI tools to improve prospecting, deal strategy, and pipeline execution while meeting revenue targets in a hybrid Tel Aviv role.

Lead design and delivery of scalable batch and real-time data pipelines, enforce engineering best practices (CI/CD, testing, observability), mentor data engineers, drive data architecture decisions (modeling, storage, compute), collaborate cross-functionally, and expand data product capabilities using cloud platforms such as Databricks and Snowflake.

Develop and deploy end-to-end machine learning models for personalized sales experiences. The role involves solving complex business problems with classic and advanced ML techniques, building agentic pipelines, working with product and engineering teams, and owning solutions from success criteria through monitoring and maintenance. Responsibilities include working with tabular, time-series, and text data, NLP, scalable ML pipelines, production deployment, and leveraging AI development tools.

Own high‑severity support escalations for a SaaS product, investigate API logs and integration workflows, run live customer sessions, coach the support team, close feedback loops with R&D, and build playbooks and automations using AI tools to prevent recurring issues.

Own and scale paid acquisition across LinkedIn, Google, and Meta to drive global pipeline and revenue. Set channel strategy, testing frameworks, and KPIs; use AI tools to optimize campaigns, collaborate with growth, sales, and RevOps, and potentially grow a team.

Lead PMM owning mid-funnel growth, pricing, and packaging to drive monetization, adoption, retention, and expansion. Define tiers, limits, and lifecycle journeys across product surfaces; partner cross-functionally and use data and AI workflows to optimize conversion and revenue.

Drive revenue by hunting and closing technical, full-cycle deals with mid-market and enterprise GTM teams. Conduct consultative discovery with senior stakeholders, convert modern GTM stacks into commercial solutions, and build custom integrations using automation, webhooks, and APIs. Leverage GenAI and LLMs (Claude) to optimize prospecting, stakeholder mapping, and pipeline execution.