Top Tech Jobs & Startup Jobs in Charlotte, NC

Build Deepgram’s governed decision layer above warehouse gold tables. Responsibilities include modeling cross-system entities, owning semantic and metrics definitions, creating agent-facing data tools and MCP surfaces, implementing data quality assertions and reconciliation checks, evaluating AI agent accuracy, and answering business questions while leaving reusable models behind. The role requires production-grade SQL and Python, semantic-layer ownership, strong data modeling judgment, AI-native workflows, clear writing, and comfort building infrastructure from scratch.

Own technical go-to-market enablement for pre-sales and post-sales teams. Build onboarding, ramp programs, technical frameworks, playbooks, certifications, launch readiness, and scalable guidance from subject-matter expertise. Partner with Product, Applied Engineering, Customer Success, Sales, and PMM to improve technical discovery, evaluations, architecture guidance, handoffs, escalations, and customer readiness. Use AI, scripts, agents, and workflows to eliminate recurring work and scale enablement.

Design and refine feature-level UI for Deepgram’s Playground and Console products. Work within the Cosmos design system, support senior designers, own assigned features through production handoff, document design rationale, participate in critiques, and provide peer feedback. The role serves technical and developer audiences and encourages practical use of AI and design tools.

Own Deepgram’s privacy operations, security compliance, audit evidence, control mapping, security questionnaires, policies, and public trust documentation. Lead DPIAs, data-flow mapping, DSAR and deletion workflows, vendor reviews, SOC 2, ISO 27001, and PCI DSS audits. Partner with Engineering, Legal, Research, and Sales Engineering to verify technical claims, automate evidence collection, maintain accurate documentation, and translate privacy and AI regulations into practical requirements and enablement.

Owns Deepgram’s privacy operations program across hosted, dedicated, and self-hosted deployments. Leads privacy risk assessments, DPIAs, transfer impact assessments, data-flow mapping, records of processing, vendor reviews, retention and deletion controls, DSAR workflows, and privacy audits. Translates privacy and AI regulations into engineering and go-to-market requirements, develops operational playbooks and tooling, supports customer reviews, and partners with Legal, Security, Engineering, and Sales Engineering to produce verifiable privacy evidence.

Build and automate security controls across bare-metal Linux infrastructure and AWS. Responsibilities include host hardening, vulnerability and patch management, container and CI/CD security, penetration testing, detection and incident response, access and log reviews, compliance evidence automation, and software supply-chain security. The role also supports customer security work and applies AI tooling to security operations.

Build AI-powered workflows, agents, integrations, and internal tools that automate People Operations. Partner with People, Engineering, and IT to modernize onboarding and other employee processes, while implementing secure access controls, human oversight, escalation paths, and production-ready architectures. Prototype with users, iterate quickly, and measure improvements in efficiency, employee experience, and operational consistency.

Partner with the SVP of Customer Success to improve executive effectiveness and organizational operating rigor. Responsibilities include calendar and meeting management, forecasting and business analytics, executive and board reporting, cross-functional initiative coordination, operating-rhythm management, action tracking, process improvement, and synthesizing data into insights, risks, decisions, and recommendations. The role combines executive support, business operations, project management, and analytical judgment.

Design and implement secure, scalable backend services for voice agents, integrate AI models and telephony, improve inference, debug concurrent systems, and collaborate with Product to deliver features end-to-end.

As the founding engineer of the Data Intelligence team, you will design semantic layers, develop AI tooling, and automate data processes to drive business insights.