Top Tech Jobs & Startup Jobs in Los Angeles, CA

Own full-cycle recruiting for Go-to-Market teams (Sales, Customer Success, Pre-Sales, Resident Engineering). Build pipelines, partner with GTM leaders on role definition and hiring strategy, deliver high-quality candidate experience, and use market intel and data to drive hiring decisions that impact revenue.

Lead a distributed global help desk of four, own end-to-end employee IT experience, manage ticketing/SLA processes, track and improve support KPIs, implement automation and AI-assisted tools, and build proactive IT support operations and processes.

The Staff Device Engineer will reverse engineer network-connected devices, architect device interaction applications, mentor engineers, and collaborate on technical challenges in industrial cybersecurity.

Seeking a Senior Cloud Infrastructure Engineer focused on cloud automation, IaC, and production reliability using AWS and GCP.

Serve as the primary post-sales trusted advisor for federal customers to drive onboarding, adoption, and value realization of Dragos solutions. Manage customer success plans and health metrics, conduct business reviews, mitigate technical/commercial risks to reduce churn, identify expansion opportunities, and collaborate with sales, TAMs, professional services, intelligence, and support.

The AI and Cloud Solutions Supervisor will lead cloud and AI engineering teams, manage cloud infrastructure, and implement AI-powered tools within a hands-on technical role.

The role involves designing and delivering a high-performance network sensor, collaborating with teams, applying systems engineering principles, and managing deployment stability in OT environments.

Lead complex cybersecurity engagements focusing on ICS/OT sectors, providing architecture reviews and threat assessments while mentoring team members.

The Intelligence and Services Operations Manager coordinates efforts between Threat Hunt, Threat Intelligence, and Services teams, ensuring operational excellence during critical events. Responsibilities include managing partnerships, facilitating intelligence sharing, identifying operational friction, and leading after-action reviews to improve processes.

The role involves applying established ML techniques to cybersecurity data problems, integrating ML outputs into data pipelines, and ensuring model reliability. Collaboration with engineers and product teams is key, along with strong communication skills and understanding of data flow.