Top Tech Jobs & Startup Jobs in Denver & Boulder, CO

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.

Design and maintain data pipelines, data contracts, and transformation layers for analytics. Model complex sources, enable observability and lineage, collaborate with product teams, and optimize data structures for scalable cybersecurity and industrial datasets.

Design, build, and deploy production ML systems for ICS/xOT cybersecurity, including threat detection, anomaly detection, NLP/LLM features, data pipelines, observability, MLOps, and containerized deployments across cloud and on-prem environments.

Lead design and modernization of scalable, secure data systems and real-time pipelines for xOT cybersecurity. Create data contracts, observability, lineage, and cross-functional solutions supporting cloud and on-prem deployments, Kubernetes, and stream processing to enable threat detection and intelligence.