Professional Services Architect

SentinelOne, Inc.; Abu Dhabi; On-site; AED 441,000 - 661,000; Full time

Job summary

SentinelOne in Abu Dhabi is seeking a Professional Services Architect to lead customer onboarding and the technical delivery of SentinelOne Endpoint solutions across on-premises, cloud and AI security. You will be a trusted advisor guiding security best practices and platform management for enterprise customers.

Own end-to-end deployments including self-hosted Kubernetes, Prompt Security, and integration with CI/CD workflows; provide governance on AI usage, data protection, and risk mitigation

Qualifications

• 5 to 8 years of enterprise cybersecurity experience in customer-facing technical roles such as Professional Services, consulting, or security engineering.
• Hands-on experience with enterprise EDR and XDR technologies including deployment, configuration, and migration from incumbent endpoint security platforms.
• Proficiency across Windows, Linux, and macOS with a strong understanding of threat detection, incident response, and SOC operations.
• Experience with cloud platforms such as AWS, Azure, and GCP as part of broader security architectures.
• Hands-on experience deploying, operating, and troubleshooting Kubernetes workloads via Helm charts.
• Knowledge of enterprise networking concepts including load balancer configuration, TLS interception, and certificate chain validation.
• Experience as Kubernetes administrator, platform engineer, or SRE supporting customer-facing, self-hosted deployments.
• DevSecOps practices including CI/CD pipelines (GitHub Actions, GitLab CI, Azure DevOps) and scripting (Python, PowerShell, Bash).
• Foundational GPU knowledge for AI workloads and awareness of AI security risks and governance frameworks.
• Relevant certifications in security, cloud, or Kubernetes (e.g., CKA) are expected.

Responsibilities

• Act as the primary consultant for customer onboarding activities related to SentinelOne Endpoint solutions and security platforms.
• Deploy and configure Prompt Security across enterprise scenarios and advise on AI governance and data protection.
• Integrate SentinelOne capabilities into CI/CD pipelines and developer workflows to support shift-left security and automation.
• Own end-to-end delivery of self-hosted customer-managed Kubernetes deployments with cluster health monitoring and disaster recovery planning.
• Provide guidance on enterprise deployment topology, capacity planning for AI workloads, and long-term operational success.

Skills

Kubernetes

DevSecOps

Cloud security

Python

GitHub Actions

EDR/XDR

Windows/Linux/macOS

AI security

Education

CKA certification

Tools

Helm

Terraform

GitHub Actions

GitLab CI

Azure DevOps

APIs

Job description

Our Purpose At SentinelOne we are driven by a clear purpose to give the advantage to those who secure our future As AI reshapes how organizations build operate and innovate the responsibility to protect them becomes more critical than ever When you join SentinelOne your work helps protect global enterprises critical infrastructure and the technologies shaping tomorrow If you are motivated by meaningful challenges and want your impact to be real measurable and global you will find purpose here About Us SentinelOne is a company at the intersection of AI and security pioneering a new operating model for cybersecurity Our AI-native platform unifies protection across endpoint cloud identity data and AI systems to deliver autonomous detection and response with clarity and speed By combining real-time analytics intelligent automation and a unified data foundation we reduce noise simplify complexity and empower security teams to focus on what truly matters Our teams are builders problem-solvers and innovators committed to shaping the future of security If you are excited to solve hard problems alongside talented mission-driven people we invite you to help us build a safer future for humanity

What Are We Looking For

We re looking for people who are relentlessly curious and committed to continuous learning AI is reshaping every function across our business and we enable every team member regardless of role or level to build fluency in AI tools and concepts Those who thrive here actively seek out new solutions experiment thoughtfully and apply what they learn to drive better faster smarter outcomes As a Professional Services Architect you will serve as the primary consultant for customer onboarding and technical delivery across SentinelOne Endpoint solutions and associated security platforms acting as a trusted advisor who guides customers on security best practices platform management and long-term success You will own end-to-end delivery of complex deployments including self-hosted Kubernetes environments and Prompt Security implementations bringing deep technical expertise across endpoint security DevSecOps cloud and AI security If you are a skilled technical practitioner who thrives in customer-facing roles and is energized by solving complex real-world security challenges this role is for you

What Will You Do

Primary responsibilities include

• Act as the primary consultant for customer onboarding activities related to SentinelOne Endpoint solutions serving as a trusted advisor on ongoing security best practices platform management and product usage while designing and implementing security architectures that integrate endpoint security DevSecOps workflows and cloud environments
• Deploy and configure Prompt Security across enterprise scenarios including employee AI tool access developer AI workflows home-grown AI applications and browser-based controls via enterprise MDM while advising customers on AI governance data protection policy enforcement and risks such as prompt injection and shadow AI usage
• Integrate SentinelOne capabilities into CI CD pipelines and developer workflows to support shift-left security practices and support customers in building automated detection response and remediation workflows including contributing to automation frameworks detection engineering and internal tooling
• Own end-to-end delivery of self-hosted customer-managed Kubernetes deployments including cluster-level installation pod-level troubleshooting and production readiness validation and advise customers on enterprise-grade deployment topology including high availability disaster recovery and cluster health monitoring
• Implement GPU-backed self-hosted deployments including capacity planning and provisioning guidance for AI ML workloads ensuring customers are set up for long-term operational success in production environments

What Skills and Knowledge Will You Bring

Ideal candidates will have 5 to 8 years of experience in enterprise cybersecurity with meaningful time in customer-facing technical roles such as Professional Services technical consulting or security engineering and solid hands-on experience with enterprise EDR and XDR technologies including deployment configuration and migration from incumbent endpoint security platforms Proficiency across Windows Linux and macOS operating systems with a solid understanding of security technologies including threat detection incident response and SOC operations along with experience with cloud platforms such as AWS Azure and GCP as part of broader security architectures Hands-on experience deploying operating and troubleshooting Kubernetes workloads via Helm charts including debugging pod-level errors startup failures and resource constraints combined with working knowledge of enterprise networking concepts such as load balancer configuration certificate chain validation and TLS interception in customer environments Prior experience as a Kubernetes administrator platform engineer or SRE supporting customer-facing or production self-hosted deployments including troubleshooting complex networking issues in enterprise or air-gapped environments is a strong advantage Experience with DevSecOps practices including CI CD pipelines such as GitHub Actions GitLab CI and Azure DevOps proficiency in scripting or automation languages such as Python PowerShell or Bash and experience working with APIs and building automation frameworks or integrations Foundational GPU knowledge including provisioning MIG splitting and VRAM allocation for AI workloads is also valued with hands-on experience supporting GPU-enabled infrastructure for AI ML workloads being a further differentiator Awareness of AI security risks including prompt injection data leakage and secure usage of GenAI tools and AI agents with experience securing GenAI or LLM-based applications including AI assistants agents or custom AI workflows and supporting AI governance compliance or risk management frameworks being a strong plus Relevant industry certifications in security cloud or Kubernetes such as CKA or equivalent are expected

What Skills and Knowledge Will You Bring?

Ideal candidates will have:5 to 8 years of experience in enterprise cybersecurity with meaningful time in customer-facing technical roles such as Professional Services, technical consulting, or security engineering, and solid hands-on experience with enterprise EDR and XDR technologies including deployment, configuration, and migration from incumbent endpoint security platforms.Proficiency across Windows, Linux, and macOS operating systems, with a solid understanding of security technologies including threat detection, incident response, and SOC operations, along with experience with cloud platforms such as AWS, Azure, and GCP as part of broader security architectures.Hands-on experience deploying, operating, and troubleshooting Kubernetes workloads via Helm charts including debugging pod-level errors, startup failures, and resource constraints combined with working knowledge of enterprise networking concepts such as load balancer configuration, certificate chain validation, and TLS interception in customer environments.Prior experience as a Kubernetes administrator, platform engineer, or SRE supporting customer-facing or production self-hosted deployments, including troubleshooting complex networking issues in enterprise or air-gapped environments, is a strong advantage.Experience with DevSecOps practices including CI/CD pipelines such as GitHub Actions, GitLab CI, and Azure DevOps, proficiency in scripting or automation languages such as Python, PowerShell, or Bash, and experience working with APIs and building automation frameworks or integrations.Foundational GPU knowledge including provisioning, MIG splitting, and VRAM allocation for AI workloads is also valued, with hands-on experience supporting GPU-enabled infrastructure for AI/ML workloads being a further differentiator.Awareness of AI security risks including prompt injection, data leakage, and secure usage of GenAI tools and AI agents, with experience securing GenAI or LLM-based applications including AI assistants, agents, or custom AI workflows and supporting AI governance, compliance, or risk management frameworks being a strong plus.Relevant industry certifications in security, cloud, or Kubernetes such as CKA or equivalent are expected.