Senior Solutions Architect - Lakewatch

Databricks Databricks · Data AI · London, United Kingdom · Field Engineering - Other

This role is for a Senior Solutions Architect focused on the Lakewatch product line at Databricks, which deals with AI/ML applications in cybersecurity. The architect will guide strategic customers in implementing big data and AI solutions, focusing on anomaly detection, behavioral analytics, and agentic AI workflows. They will collaborate with account teams, provide technical leadership, enable clients through workshops and POCs, and influence the product roadmap by translating field insights into strategic recommendations. The role requires strong experience in cybersecurity engineering, SIEM platforms, and designing customer-facing security solutions, with an emphasis on data and AI applications within cybersecurity.

What you'd actually do

  1. Provide technical leadership to guide strategic customers to successful implementations on big data projects, ranging from architectural design to data engineering to model deployment
  2. Collaborate with GTM leadership and account teams to design and execute high-impact engagement strategies across your territory, driving Lakewatch adoption from initial data offload through full SIEM augmentation or replacement.
  3. As a trusted advisor, serve as an expert Solutions Architect building technical credibility with CISOs, security architects, SOC leadership, and security analysts to drive product adoption and vision.
  4. Enable clients at scale through workshops, POC execution, and developing customer-facing collateral that increases technical knowledge and demonstrates the value of an open agentic SIEM architecture.
  5. Influence product roadmap by translating field-derived, data-driven insights into strategic recommendations for Product and Engineering teams.

Skills

Required

  • 5+ years of cybersecurity engineering, security operations (SecOps), or security architecture expertise
  • Proven track record of designing and delivering customer-facing security solutions
  • 3+ years in a customer-facing, pre-sales or consulting role
  • Experience with design and implementation of data and AI applications in cybersecurity
  • Experience with anomaly detection, behavioral analytics, and agentic AI workflows for triage and investigation
  • Deep familiarity with SIEM platforms (Splunk, Microsoft Sentinel, QRadar, or similar)
  • Experience with "detection-as-code" workflows
  • Proficient in programming, debugging, and problem-solving using SQL and Python
  • Hands-on experience building solutions within major public cloud environments (AWS, Azure, or GCP)
  • Deep experience in security operations
  • Broad familiarity across one or more of the following: data engineering, data warehousing, AI/ML for security, data governance, and streaming.

Nice to have

  • Familiarity with SOAR platforms
  • Undergraduate degree (or higher) in a technical field such as Computer Science, Cybersecurity, Applied Mathematics, Engineering or similar.

What the JD emphasized

  • 5+ years of cybersecurity engineering, security operations (SecOps), or security architecture expertise, with a proven track record of designing and delivering customer-facing security solutions (of which 3+ years are in a customer-facing, pre-sales or consulting role).
  • Experience with design and implementation of data and AI applications in cybersecurity, including anomaly detection, behavioral analytics, and agentic AI workflows for triage and investigation.
  • Deep familiarity with SIEM platforms (Splunk, Microsoft Sentinel, QRadar, or similar), including deployment, tuning, detection engineering, and migration strategies.

Other signals

  • AI/ML applications in cybersecurity
  • agentic AI workflows
  • SIEM augmentation or replacement
  • customer-facing security solutions