Technical Support Engineer – L2

• Own escalated cases end-to-end, including root cause analysis, resolution, and customer confirmation
• Investigate issues across conversational AI flows, voice integrations, REST APIs, webhooks, and core banking connectors
• Identify and categorize AI behavior gaps involving hallucination, intent misclassification, knowledge coverage, flow misconfiguration, and integration issues
• Debug using logs, call recordings, digital transcripts, API traces, and observability tooling
• Analyze escalated AI conversations and categorize root causes for ML and Product teams
• Write, refine, and retire knowledge base articles to improve AI resolution rates
• Engage directly with customer technical and operational stakeholders via email and calls
• Acknowledge, prioritize, and resolve escalated tickets in Salesforce Service Cloud
• Lead P1/P2 incident response, including war room coordination, timestamped updates, and stakeholder management
• Write post-mortems for customer leadership and compliance review
• Maintain audit-ready case documentation in Salesforce Service Cloud
• File actionable bug reports for Engineering
• Surface recurring patterns as structured insights to Product and ML teams
• Immediately flag compliance-adjacent issues involving call recording, disclosure language, and member data

• 5+ years in technical or implementation support at a B2B SaaS company
• REST API and webhook debugging, including auth failures, integration traces, and event-driven architecture
• Postgres/SQL for session data queries, usage patterns, and data integrity validation across integrated systems
• Python scripting for diagnostic scripts, log parsing, and lightweight internal tooling
• Experience with observability platforms such as OpenSearch, Kibana, Grafana, Datadog, or equivalent
• Familiarity with queries, dashboards, and distributed traces
• Voice channel familiarity with SIP and IVR routing; ability to distinguish ASR errors from AI model errors
• Salesforce Service Cloud or similar experience with case management, escalation tracking, and audit-trail documentation
• Hands-on experience with AI agent creation and orchestration, including configuring agents, chaining tools, defining guardrails, and debugging multi-step workflows
• Proficiency with Cursor and Claude Code for investigations, codebase exploration, and scripting
• Ability to critically evaluate AI conversation transcripts across voice and digital channels
• Clear written and verbal communication with technical and non-technical customer stakeholders
• Precise, audit-ready documentation
• Highly self-directed; able to manage own queue without supervision
• Familiarity with Kubernetes is a plus

• Remote-first work arrangement
• Comprehensive benefits
• High ownership environment
• AI innovation at the frontier of financial services