Top Tech Jobs & Startup Jobs in Charlotte, NC

Build and scale secure data lakehouse and warehouse infrastructure supporting analytics, machine learning, clinical AI performance monitoring, and self-service insights. Develop scalable data pipelines, models, orchestration, quality controls, and LLM-enabled analytics tools using heterogeneous clinical and EHR data. Collaborate with engineering, data science, clinical, product, and client success teams to establish trustworthy metrics and technical solutions.

Own full-cycle recruiting across technical and non-technical functions, with emphasis on engineering, data science, and AI/ML hiring. Lead proactive sourcing, market mapping, candidate progression, hiring manager partnerships, offer closing, ATS administration, recruiting analytics, verification processes, and workflow improvement. The role also establishes recruiting metrics, structured interviews, scorecards, interviewer training, and inclusive talent pipelines in a high-growth startup.

Own product marketing across sales enablement, deal-specific content, competitive intelligence, module launches, buyer messaging, and customer expansion. Develop positioning, messaging, sales collateral, battlecards, and executive materials for health system buyers, translating clinical and technical value into compelling business cases. Partner closely with Sales, Product, Client Success, and Clinical teams in a remote startup environment.

The Infrastructure Engineer will build and maintain cloud infrastructure, develop CI/CD pipelines, ensure security compliance, and optimize system performance for healthcare applications.

Build and deploy integrations between the Bayesian platform and large EHR systems, implement automated integration and end-to-end tests, support production deployments and go-lives, develop tooling and automation (including LLMs), and collaborate with implementation and clinical teams to deliver clinician-facing workflows.

Build and maintain data integration interfaces and ingestion pipelines between EHR systems and the Bayesian platform. Collaborate with client technical teams, implement automated integration tests, deploy and support go-lives, troubleshoot data correctness end-to-end, and develop tooling and automation (including LLM-driven) to scale integrations.

Lead revenue growth by developing and executing sales strategies, managing relationships with healthcare executives, and mentoring teams to exceed targets.

Develop and tune ML models, productionize and deploy strategies for ML systems, and align cross-functionally to communicate performance metrics.

As a Staff Machine Learning Engineer, you will develop, productionize, and deploy ML models for clinical use, ensuring real-world effectiveness through hands-on coding and infrastructure building.

As Director of AI/ML, lead the ML organization, set technical vision, mentor a high-performing team, and contribute to model development and production deployment.