Top Tech Jobs & Startup Jobs in Charlotte, NC

Leads OT incident response investigations as Incident Commander, including triage, threat hunting, compromise assessments, root-cause analysis, and customer advisory work. Develops incident response plans, playbooks, maturity assessments, and tabletop exercises; manages customer relationships and communications; contributes to threat research and thought leadership; mentors responders and improves IR methodologies. The role requires extensive ICS/OT cybersecurity, digital forensics, consulting, incident management, and communication experience.

Lead large-scale Linux sensor platform initiatives for high-performance OT and ICS network monitoring. Design and improve packet ingestion, capture pipelines, queue management, broker integration, observability, and reliability. Own production root cause analysis, postmortems, performance benchmarks, and durable fixes. Translate business goals into technical plans, establish engineering standards, mentor team members, and guide architecture across the sensor codebase.

Build and maintain lead-to-order business systems across Salesforce and connected platforms. Design complex applications, declarative automation, Apex and Lightning solutions, integrations, APIs, data models, and security controls. Remediate technical debt, lead migrations and tool rollouts, manage testing and cutovers, and ensure production systems are observable, documented, and governed. Partner cross-functionally to translate business requirements into scalable solutions while supporting AI capabilities in go-to-market workflows.

Develop and validate high-fidelity threat detections and asset-identification analytics for industrial control system environments. Analyze threat intelligence, packet captures, host logs, network and device artifacts, and large datasets to identify adversary behaviors. Mentor detection engineers, review and triage detection requests, document analytics processes, and partner with engineering and quality teams to address platform gaps. Support ICS cyber-range activities and contribute to detection testing, tuning, and knowledge-base maintenance.

Designs and manages scalable data pipelines, contracts, transformation layers, and analytics models. The role focuses on data governance, observability, lineage, configuration validation, and collaboration with product engineering teams. It requires processing large datasets, integrating cloud and on-premises industrial technologies, and implementing streaming and message-queuing solutions, ideally in cybersecurity or industrial environments.

Design and maintain data pipelines, models, and transformation layers for analytics. Build data contracts, observability and lineage tooling, collaborate with product engineering, and optimize data structures for performance and scalability.

Lead and grow a data engineering team building and modernizing the core data platform for cybersecurity products. Define technical strategy and data models, ensure data quality for detection and analytics, champion AI-assisted engineering, oversee production support and incident response, collaborate with cross-functional teams, and drive hiring and best practices to deliver scalable, high-performance data pipelines and storage.

Design and implement scalable data integrations and transformation layers for cybersecurity products. Build data contracts, dimensional/incremental models, observability, and lineage tooling. Collaborate with product engineering to integrate SIEMs (Sentinel, Splunk) and deploy cloud/on-prem solutions on Kubernetes/Docker, processing medium-to-large datasets and stream/message systems.

Lead and grow the Backend Engineering team building microservice-based platform components for streaming data ingest, detection processing, baseline learning, asset reconciliation, and core platform APIs. Mentor engineers, collaborate with tech leads and product managers, provide technical design input, support production deployments, and occasionally contribute to development and troubleshooting.

Design, build, and deploy production-grade ML systems for ICS/xOT cybersecurity, including threat detection, anomaly detection, NLP/LLM applications, and scalable data pipelines with observability and MLOps practices for cloud and on-prem environments.