Top Tech Jobs & Startup Jobs in Charlotte, NC

Build and maintain scalable ELT pipelines, dbt models, semantic layers, and governed product analytics assets. Partner with Data Engineering, Product Engineering, Data Governance, analysts, and product managers to define trusted metrics, monitor data quality, document taxonomies, and support self-service analytics. Translate product usage telemetry into certified metrics for expansion and upsell analysis, while communicating technical concepts to technical and non-technical stakeholders and driving engineering best practices.

Leads customer support programs and supportability across Support, Product, and Engineering. Owns process optimization, automation, analytics, dashboards, supportability standards, product readiness reviews, root-cause analysis, and roadmap influence. Drives measurable improvements in customer satisfaction, deflection, resolution times, support efficiency, and product troubleshooting capabilities while contributing to strategic planning, budgeting, and technology decisions.

Owns enterprise customer onboarding from sales handoff through production deployment within 30 days. Leads kickoff and implementation planning, resolves cloud, Linux, networking, container, identity, and security issues, configures NodeZero testing, performs root-cause analysis, and creates reusable support documentation. Collaborates with Customer Success, Engineering, Product, and Sales while occasionally supporting escalated cases and mentoring junior engineers.

Build and operate backend APIs, a reusable integration platform, security-tool connectors, MCP capabilities, and event-driven services. Own GraphQL federation, permissions, multi-tenant access, reliability, observability, vendor API resilience, and production operations. Collaborate across engineering, product, and security teams while mentoring other engineers and contributing to technical standards.

Build and operate backend services for licensing, entitlements, provisioning, access control, multi-tenant administration, MSP/MSSP workflows, audit logging, and notifications. Design reliable cloud-native systems using Docker, Kubernetes, and relational databases, while contributing to observability, incident response, documentation, testing, and platform security. Collaborate across engineering, product, and design teams and mentor less experienced engineers.

Build backend APIs, GraphQL services, ETL pipelines, event-driven systems, and distributed infrastructure for cybersecurity workflows involving vulnerability intelligence, EDR validation, deception, tripwires, and autonomous defense. The role includes production reliability, monitoring, incident response, debugging, customer-facing security features, and collaboration with engineering and product teams. The engineer will also mentor less experienced developers and ensure security automation is safe, explainable, and reversible.

Own and evolve the company-wide SRE strategy, reliability standards, observability practices, incident management, service ownership, SLOs, and on-call operations. Lead cross-functional reliability initiatives, establish dashboards, alerts, runbooks, and escalation paths, improve production readiness and incident response, and operate large-scale distributed systems across AWS and Kubernetes. Participate in a 24/7 on-call rotation and help shape the SRE function.

Lead the architecture and operation of Horizon3’s developer experience platform, including local development, CI/CD, build systems, container images, artifact promotion, release workflows, security gates, and delivery observability. Build reusable tooling and paved paths, establish secure AI-assisted development practices, improve reproducibility and supply-chain security, and mentor engineers. Partner across Platform, Security, QA, and application teams to drive adoption, reliability, delivery speed, and continuous improvement.

Lead the design and operation of AWS and Kubernetes platforms, infrastructure automation, CI/CD, observability, security, and developer self-service capabilities. Drive cross-team platform initiatives, establish technical standards, improve reliability and operational practices, participate in incident response, mentor engineers, and guide architecture for regional and ephemeral environments.

Own the production lifecycle for machine learning and LLM-backed systems, including training and post-training pipelines, inference serving, model releases, monitoring, retrieval infrastructure, and cost and latency optimization. Partner with AI researchers and engineering teams to move prototypes into reliable production capabilities across customer tenants. Develop ETL and GraphQL features, enforce tenant isolation, and support deployments in regulated or customer-controlled environments.