Founding Customer Success Engineer

Designs and implements AI-driven solutions for digital marketing use cases, bridging technical AI capabilities with marketing needs. Requires expertise in ML model development, API integration, and understanding of marketing technology stacks.

Drive customer success, onboarding, and retention for SaaS clients. Provide strategic digital marketing guidance and act as a trusted advisor. Requires account management experience and digital marketing expertise.

Work directly with customers to implement and customize CallMiner's conversation intelligence platform, ensuring successful deployment and integration. Provide technical expertise and support to drive customer success.

This role owns deployment and activation success for a portfolio of customers, embedding deeply into their organizations to drive AI adoption. The lead builds champion networks, runs workshops and training sessions, and designs activation strategies that turn AI investment into measurable outcomes. They partner with transformation leads to identify the right capabilities for each use case.

This role focuses on selling Minerva's AI marketing platform to mid-market companies. The account executive will manage a pipeline of prospects, conduct product demonstrations, and close deals. Responsibilities include understanding client marketing workflows, building business cases, and driving revenue growth.

This Forward Deployed Engineer role at Minerva involves working directly with customers to deploy and customize AI agents that automate marketing workflows. The engineer will build integrations, develop custom solutions, and ensure the platform meets specific client needs in real-world environments. This role requires strong software engineering skills, experience with APIs, and the ability to work closely with clients to solve complex technical challenges.

This role focuses on building and scaling data ingestion pipelines to support AI-driven marketing analytics. The engineer will design robust data collection systems, ensure data quality, and optimize streaming and batch processing. Key technologies include Kafka, Spark, Airflow, and cloud services.