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Develop and scale backend systems for automating Security Analyst tasks, leveraging AI to neutralize digital threats swiftly, and mentoring junior engineers.

Doppel seeks an experienced backend engineer to develop scalable infrastructure for their AI-native social engineering defense platform, focusing on efficient data handling and service standardization.

The Forward Deployed Engineer manages enterprise onboarding and API integrations, ensuring platform adoption through strong communication and technical skills, with a focus on troubleshooting and project management.

As a Machine Learning Engineer at Doppel, you will design, train, and deploy ML models for detecting malicious content, ensuring scalability and real-time performance while collaborating with teams and stakeholders.

Doppel seeks engineers for their AI-native social engineering defense platform, focusing on customer-driven solutions and scalable systems monitoring digital threats.

Seeking a fullstack engineer to develop a new Simulation product that includes creating phishing simulations and voice deepfakes using AI.

Build and maintain a shared frontend platform and design-to-production pipeline: application shell, data layer, routing, auth, component library, agent-driven code generation, observability, and packaging so product teams ship without hand-writing frontend code.

Improve and operationalize detection workflows by designing, testing, and optimizing sourcing queries, collection methods, enrichment logic, and alerts. Partner with Product and Engineering to relay customer feedback and threat trends, analyze recurring alert patterns to inform scalable improvements, and support onboarding and ongoing detection implementations for select customers.

Lead and grow a forward-deployed engineering team that deploys Doppel with enterprise customers, owns enterprise integrations (SIEM/SOAR, SSO/SCIM, REST APIs, webhooks), scopes pre-sale integrations, productizes bespoke work, and coordinates across engineering, product, and sales to accelerate deployments.

Design, train, and deploy machine learning models for detecting malicious content, working with large datasets and collaborating with teams to enhance system scalability.