Top Remote Senior Level Jobs

Lead end-to-end business hiring for Operations, Support, and G&A at an early-stage healthcare startup. Build outbound sourcing pipelines, partner with hiring managers, improve hiring processes and scorecards, maintain candidate experience, and report hiring insights and market feedback.

The Strategic Account Executive will drive enterprise sales, manage a dynamic sales pipeline, engage with C-level executives, and negotiate multi-year contracts in the Insurance and Wealth sector.

The Field Application Engineer will support global customers in design-in activities, develop product solutions, optimize power consumption, and assist with customer HW/SW development.

As a Senior Data Scientist, you'll develop fraud detection models, perform detailed analyses, and work closely with teams to drive product innovation and business outcomes.

The Lead Infrastructure Engineer will define and build infrastructure at Atticus, managing platforms, security, reliability, and empowering engineering teams.

The Associate General Counsel will manage legal matters including contracts, regulatory analysis, and product counseling, supporting Vetcove's growth and legal strategy.

Lead design and build of scalable, resilient backend systems for Gusto Money products. Own projects end-to-end, adopt AI tooling, collaborate cross-functionally, and mentor engineers while driving product development from concept to launch.

Lead and coach Territory Managers across the Southeast, drive regional revenue and pipeline accuracy, maintain Salesforce hygiene and forecasting, localize national strategy, recruit and develop talent, and spend the majority of time in-field (~60% travel) supporting customer engagements and scaling sales operations.

Lead design and scaling of the data platform and analytics pipelines. Build and maintain ETL/ELT workflows, integrations, serverless data services, and reliable data models. Mentor teammates, improve automation, observability, and data governance to support analytics and operational insights.

Design, build, and own scalable data pipelines and evaluation systems that power production AI features and internal analytics. Ensure data quality across ingestion, modeling, and reporting, collaborate with ML and analytics teams, deploy and monitor ML systems, and establish standards for data work and evaluation.