• Pre-sales: Assist in qualifying sales leads from a technical standpoint, understanding customer requirements, and providing relevant technical information • Sales calls: Serve as the primary technical resource during sales calls, addressing customer inquiries, educating them about features, specifications, and functionality, as well as integration possibilities • Demonstrate proficiency in networking applications and solutions, highlighting the value proposition of Fortinet products and services • Post-sales: Act as the main technical contact for assigned accounts, actively engaging with the technical support team and engineering to promptly address and resolve customer's technical issues • Provide post-sales training and ongoing assistance to customers, ensuring they can effectively utilize Fortinet solutions • Travel throughout the territory to support the needs of the business.

Role Description This is a remote position. Must Have: - Japanese certification level: JLPT N2 level Job Description during training period: - AccuKnox Pre-Sales Engineering Support: Provide support to customers, partners in supporting Demos, POC (Proof of Concept). - AccuKnox Product Marketing Support: Provide support in the area of Product Marketing - Data Sheets, White Papers, Blogs, Videos, Collaterals. - Security Research: Understand industry compliance, governance standards (PCI, SOC2, GDPR, CCPA, HIPAA), Security Frameworks (MITRE, CIS, OWASP, NIST STIGs), Current and Emerging Threats, Attack vectors (Ransomware, Bitcoin, Zero day). - AccuKnox Product Testing: Play the role of “voice of customer” in AccuKnox product testing. Qualifications - BE, B.Tech, MCA, MSC in Computer Science - Knowledge of Public Cloud platforms (AWS, Azure, GCP) preferred - MBA preferred - Excellent written, verbal, presentation, communication skills Requirements - Knowledge, Experience, Certifications - Cloud Platforms: GCP, AWS, Azure, Kubernetes, Openstack, Linux - CyberSecurity Products: Aqua, Tigera, Twistlock, Sysdig, Trivy, Clair, Snyk, Anchore, WireShark - Development Tools/Languages: Python, Golang, Java, SQL, NoSQL, NumPY - Certifications: CKA, CKAD, CKS - Compliance, Governance Frameworks: Governance standards (PCI-DSS, SOC2, GDPR, CCPA, HIPAA) - Security Frameworks (MITRE, CIS, OWASP, NIST, STIGs) - Excellent Communication Skills - Written, Verbal [Word, Excel, PPT, Zoom] Benefits - Bonus points for: - Open Source Contributions - Experience operating in a 24X7 SOC - Writing insightful blogs, white papers - Presentations at RSA, BlackHat, DefCon, BSides, etc. - Terraform and/or Ansible, Vault a plus

Role Description Lead delivery of AI and intelligent automation solutions across prioritized use cases, owning execution, technical quality, architecture integrity, release readiness, delivery scope, timelines, success criteria, risks, dependencies, and technical trade-offs to ensure successful outcomes. - Translate business problems into AI designs, user stories, technical specifications, and IT design specifications using systems thinking, workflow analysis, user journey analysis, and structured problem decomposition. - Lead iterative prototyping, pilot development, and rapid experimentation to validate solution hypotheses, while ensuring every pilot is designed with a clear and practical path to scalable, maintainable, enterprise-grade production deployment. - Provide solution architecture leadership across AI and agent-based patterns, including retrieval-augmented generation, orchestration, copilots, integrations, data flows, and cloud or platform alignment to ensure solutions are scalable, secure, compliant, interoperable, and maintainable. - Guide teams in building production-ready AI and automation solutions by supporting API integrations, data pipelines, transformations, workflow orchestration, deployment practices, and engineering standards for performance, reliability, and monitoring. - Ensure required EARB and AIRB approvals are obtained and validate solution quality by reviewing test cases, confirming control adherence, supporting governance and compliance requirements, and establishing appropriate operational monitoring. - Partner with product, architecture, security, data governance, engineering, and operations teams to align requirements, maintain delivery transparency, manage dependencies, and support structured transition to production support and ongoing operations. - Responsible for key deliverables, including technical specifications, AI solution designs, user stories, IT Design Specification, test case reviews, EARB and AIRB submissions, architecture documentation, implementation artifacts, operational guides, and knowledge transfer materials. Qualifications - Bachelor's Degree - At least 10 years of experience in technology delivery and solution implementation - Generative AI, large language models, machine learning, and agentic architecture patterns such as retrieval-augmented generation, orchestration, and copilots. - Intelligent automation, enterprise integration patterns - AI governance, security and compliance frameworks - Enterprise architecture principles, and production delivery practices in regulated or controlled environments. - Strong solution architecture capability across AI, data, cloud, and enterprise systems, with the ability to translate business problems into implementable solution designs, user stories, and technical specifications. - Proven delivery leadership, prototyping and pilot-to-production execution, stakeholder communication, governance coordination, test case review, control validation. - Strong engineering oversight for APIs, data pipelines, deployment, monitoring, and operational readiness. - Ability to operate across problem framing, solution design, architecture leadership, governance, and end-to-end delivery execution in ambiguous environments. - Ability to balance rapid experimentation with enterprise-grade rigor, influence matrixed teams, drive clarity and accountability, and ensure solutions are scalable, secure, maintainable, and ready for production support. Requirements - This is a remote position based in the United States. Relocation is not available. Benefits - Comprehensive benefits to support physical, mental, and financial well-being. - Competitive compensation package determined by performance, experience, skills, equity, regular job market evaluations, and geographical markets. - Other compensation, such as an annual bonus or long-term incentive opportunities may be offered.

Role Description Lead delivery of AI and intelligent automation solutions across prioritized use cases, owning execution, technical quality, architecture integrity, release readiness, delivery scope, timelines, success criteria, risks, dependencies, and technical trade-offs to ensure successful outcomes. - Translate business problems into AI designs, user stories, technical specifications, and IT design specifications using systems thinking, workflow analysis, user journey analysis, and structured problem decomposition. - Lead iterative prototyping, pilot development, and rapid experimentation to validate solution hypotheses, while ensuring every pilot is designed with a clear and practical path to scalable, maintainable, enterprise-grade production deployment. - Provide solution architecture leadership across AI and agent-based patterns, including retrieval-augmented generation, orchestration, copilots, integrations, data flows, and cloud or platform alignment to ensure solutions are scalable, secure, compliant, interoperable, and maintainable. - Guide teams in building production-ready AI and automation solutions by supporting API integrations, data pipelines, transformations, workflow orchestration, deployment practices, and engineering standards for performance, reliability, and monitoring. - Ensure required EARB and AIRB approvals are obtained and validate solution quality by reviewing test cases, confirming control adherence, supporting governance and compliance requirements, and establishing appropriate operational monitoring. - Partner with product, architecture, security, data governance, engineering, and operations teams to align requirements, maintain delivery transparency, manage dependencies, and support structured transition to production support and ongoing operations. - Responsible for key deliverables, including technical specifications, AI solution designs, user stories, IT Design Specification, test case reviews, EARB and AIRB submissions, architecture documentation, implementation artifacts, operational guides, and knowledge transfer materials. Qualifications - Bachelor's Degree - At least 10 years of experience in technology delivery and solution implementation - Generative AI, large language models, machine learning, and agentic architecture patterns such as retrieval-augmented generation, orchestration, and copilots. - Intelligent automation, enterprise integration patterns - AI governance, security and compliance frameworks - Enterprise architecture principles, and production delivery practices in regulated or controlled environments. - Strong solution architecture capability across AI, data, cloud, and enterprise systems, with the ability to translate business problems into implementable solution designs, user stories, and technical specifications. - Proven delivery leadership, prototyping and pilot-to-production execution, stakeholder communication, governance coordination, test case review, control validation. - Strong engineering oversight for APIs, data pipelines, deployment, monitoring, and operational readiness. - Ability to operate across problem framing, solution design, architecture leadership, governance, and end-to-end delivery execution in ambiguous environments. - Ability to balance rapid experimentation with enterprise-grade rigor, influence matrixed teams, drive clarity and accountability, and ensure solutions are scalable, secure, maintainable, and ready for production support. Requirements - This is a remote position based in the United States. Relocation is not available. Benefits - Comprehensive benefits to support physical, mental, and financial well-being. - Competitive compensation package determined by performance, experience, skills, equity, regular job market evaluations, and geographical markets. - Other compensation, such as an annual bonus or long-term incentive opportunities may be offered.