Technical Platform Expert - Stockholm

Legora Legora · Vertical AI · Stockholm, Sweden · Customer Enablement

This role is the final technical authority on the AI platform's behavior in the real world, focusing on investigating and resolving complex technical escalations, validating the platform before release, and identifying systemic issues. The role acts as a bridge between support, product, and engineering, advocating for improvements and driving root cause analysis for incidents. It requires deep understanding of LLM failure modes and strong analytical skills, without direct coding responsibilities.

What you'd actually do

  1. Own the hardest problems: Take the deepest technical escalations from across the function and drive them to root cause through rigorous log, data, and system-level analysis.
  2. Validate the platform before it ships: Support beta testing and pre-GA investigations. Identify where real platform behavior diverges from the spec, pressure-test workflows under real conditions, and deliver findings to Product Operations with clear reproduction steps before they become customer-facing incidents.
  3. Detect and declare systemic events: Identify when individual tickets share a common root cause and trigger coordinated incident response before volume makes the pattern undeniable. Own the signal that turns a cluster of cases into a declared Sev1 or Sev2 incident.
  4. Be the AI subject-matter expert: Serve as the expert on platform behavior and AI output patterns, including accuracy, retrieval quality, document processing, and anomalous output.
  5. Be the support function's voice in Product and Engineering: Bring the real-world pattern of platform failures into product reviews, release planning, and engineering discussions. Surface what the support tiers see that Product Operations does not, and advocate for the diagnostic tooling, observability improvements, and platform fixes that make the function faster and the product more reliable.

Skills

Required

  • deep technical support, solutions, or a platform-specialist role
  • rigorous about the root cause
  • logs, data, and systems analysis
  • understand how LLM and AI systems behave, including how failure modes present to users
  • translate technical findings clearly
  • effective in cross-functional settings
  • composed under pressure
  • experience working major escalations
  • think in patterns across cases

Nice to have

  • background in legal AI
  • document processing
  • retrieval-augmented systems

What the JD emphasized

  • final technical authority
  • not writing code
  • rigorous log, data, and system-level analysis
  • real platform behavior diverges from the spec
  • AI subject-matter expert
  • platform failures
  • technical root cause
  • diagnostic tooling, test frameworks, and automation

Other signals

  • AI-native workspace
  • analysing thousands of documents in minutes
  • powering end-to-end workflows
  • understanding how LLM and AI systems behave
  • legal AI