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Artificial Intelligence • Big Data • Cloud • Information Technology • Software • Big Data Analytics • Automation
Lead Dynatrace's global Customer Education, defining AI-driven learning and enablement strategy to accelerate adoption, retention, and growth. Build enterprise adoption programs, oversee Dynatrace University (digital, instructor-led, certifications), embed enablement across customer lifecycle, track KPIs linking education to business outcomes, and develop a high-performing global team while influencing senior stakeholders.
Top Skills:
AIAnalyticsCloud PlatformsDigital Adoption PlatformsLearning TechnologiesObservabilityProduct Usage Data
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Consumer Web • eCommerce • Machine Learning • Software • Sports • Analytics
Design, build, and operate scalable AWS-based backend services and APIs for the Collectors Vault. Own architecture and delivery, improve performance and reliability, mentor engineers, and leverage modern AI tools to accelerate development and engineering velocity.
Top Skills:
APIsAWSC#Claude Code CliCodexEvent-Driven ArchitecturesJavaServerless
Consumer Web • eCommerce • Machine Learning • Software • Sports • Analytics
Lead backend and full-stack work on the Payments team, building multi-gateway integrations (Stripe, PayPal), payment APIs, and customer payment UIs. Ensure secure, compliant (PCI-DSS) payment flows, reliability, observability, and scalability across AWS/Kubernetes microservices. Partner cross-functionally to design architecture, implement settlement/reconciliation, and maintain high availability.
Top Skills:
.NetAi-Assisted Development ToolsAWSC#DatadogDynamoDBKafkaKubernetesPaypalPci-DssPostgresReactStripeSvelteTypescript
The Cyber AI Engineer will drive the development and optimization of advanced tools, processes, and workflows to predict, detect, and prevent AI-specific threats. This hands-on technical leadership role combines deep research in AI security with close collaboration across teams to integrate AI security capabilities into robust cybersecurity architectures
Key Responsibilities:
• Design, develop, and optimize AI-security-specific threat models, tools, and solutions for threat identification, prediction, and prevention.
• Implement and secure machine learning models, GenAI models, and AI techniques to enhance threat detection, monitoring, and risk scoring.
• Integrate AI security tools and technologies across cybersecurity architectures, collaborating with data scientists, security engineers, and other stakeholders.
• Analyze AI security incident data to refine and improve AI models and methodologies.
• Provide technical leadership and mentorship to junior engineers in AI and machine learning.
• Ensure alignment and compliance with industry standards (NIST AI-RMF, ISO 42001, OWASP Top 10 for LLMs) and advanced security architectures (Agentic, MCP).
• Stay abreast of emerging trends and advancements in AI and cybersecurity.
Required Qualifications:
• A Bachelor’s or Master’s degree in Computer Science, Engineering, or a closely related discipline is required.
• 5+ years of experience in AI-focused cybersecurity in an enterprise environment.
• Expertise in Python, R, Java, or similar programming languages.
• Deep understanding of machine learning, neural networks, and application to security systems.
• Hands-on experience with AI security technologies (intrusion detection, anomaly detection, threat intelligence).
• 3+ years’ experience in Azure or AWS cloud-native services, architectures, and tools.
• Expertise in enterprise architectures (including cloud-native and AI architecture patterns).
• Advanced knowledge of security and governance frameworks (NIST AI-RMF, ISO 42001, OWASP Top 10 for LLM).
• Strong communication and collaboration skills.
Preferred Qualifications
• Experience with implementing OWASP Top 10 LLM Threats in practice with any industry or open-source product.
• Working experience in Threat Modeling
• Experience with agentic and Model Context Protocol (MCP) architectures.
• Demonstrated ability to lead cross-functional technical teams.
• Track record of published research or thought leadership in AI security.
Phizenix Livermore, California, USA Office
101 E. Vineyard Ave, Suite #119–115, Livermore, CA , United States, 94550
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
