Staff Professional Services Architect (AI SIEM/HA)

Please note that under Federal & FedRAMP regulations, hiring for this role is limited to US citizens only. 

FedRAMP staff may be subject to customer or third-party background checks, up to and including a secret clearance, if required by their role at SentinelOne. 

As a Staff Professional Services Architect, you will lead the technical transition from pre-to-post sales, defining project plans and drafting SOWs for complex implementations. You will design scalable ingestion pipelines and automation workflows for AI SIEM and SOAR platforms, ensuring data normalization across the security stack. Serving as a technical mentor and escalation point, you will partner with Product and Engineering to align field feedback with the platform’s strategic roadmap.

What will you do?

As a Professional Services Architect within SentinelOne’s Professional Services organization, you will play a critical role in the successful scoping and delivery of complex, cross-platform cybersecurity product implementations, particularly in the areas of AI-powered SIEM and SOAR. This is a customer-facing, post-sales role where you will serve as a trusted advisor, working closely with sales, delivery consultants, and customer stakeholders to ensure successful outcomes and high satisfaction.

Your primary responsibilities will include:

• Scoping Engagements: Collaborate with sales, partners, and customers to define implementation plans, estimate effort, and create Statements of Work (SOW). Align services to customer needs across SentinelOne product lines, with a focus on AI SIEM and Hyperautomation/SOAR.
  
  
• Solution Design: Architect scalable, secure solutions across SentinelOne’s platform, including the design of AI SIEM data ingestion pipelines, parsing strategies, schema normalisation, and automation workflows that support end-to-end detection and response.
  
  
• AI SIEM Architecture & Normalisation: Define and validate architectural patterns for high-volume data ingestion, telemetry normalisation, parser requirements, and enrichment workflows to ensure consistent, high-fidelity data for analytics and automation.
  
  
• Collaborate with Product Management and Engineering: Partner with the AI SIEM Product team to evaluate new use cases, data models, and integration patterns, ensuring alignment between customer requirements, platform capabilities, and Professional Services delivery readiness.
  
  
• SME L