Technical Support Engineer - L2

interface.ai

5d•Remote

About The Position

Interface.ai builds Generative AI-powered virtual assistants for banks and credit unions, automating customer service across voice and chat for over 100 financial institutions. Our AI agents handle the majority of member interactions autonomously. The L2 role is for technically complex, compliance-sensitive, or business-critical escalations. The engineer in this role will own escalations end-to-end, drive AI quality improvement through case resolution, and serve as a trusted technical partner to customers with high expectations.

Requirements

5+ years in technical or implementation support at a B2B SaaS company
REST API and webhook debugging: auth failures, integration traces, event-driven architecture
Postgres/SQL: session data queries, usage patterns, data integrity validation across integrated systems
Python scripting: diagnostic scripts, log parsing, lightweight internal tooling
Observability platforms: OpenSearch, Kibana, Grafana, Datadog or equivalent; queries, dashboards, distributed traces
Voice channel familiarity: SIP, IVR routing, distinguishing ASR errors from AI model errors
Salesforce Service Cloud or similar: case management, escalation tracking, audit-trail documentation
Hands-on with AI agent creation and orchestration: configuring agents, chaining tools, defining guardrails, debugging multi-step workflows
Proficient with Cursor and Claude Code for investigations, codebase exploration, and scripting
Able to critically evaluate AI conversation transcripts across voice and digital channels
Clear written and verbal communication with both technical and non-technical customer stakeholders
Precise, audit-ready documentation: every case record should be readable by someone who wasn't in the conversation
High Agency: you drive issues to resolution independently, make judgment calls without waiting to be told, and take full ownership of outcomes from intake to close
Highly self-directed: manages own queue, no supervision needed

Nice To Haves

Familiarity with Kubernetes: reading pod logs, understanding deployment states, and navigating cluster context during incident investigation is a plus

Responsibilities

Own escalated cases end-to-end: root cause, 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 across 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, categorize root causes with enough specificity for ML/Product to act on, and close the feedback loop
Write, refine, and retire knowledge base articles to continuously raise AI resolution rates
Engage directly with customer technical and operational stakeholders via email and calls
Ensure timely acknowledgment, prioritization, and resolution of escalated tickets in Salesforce Service Cloud
Lead P1/P2 incident response: war room coordination, timestamped updates, parallel stakeholder management across Engineering and customer teams
Write post-mortems suitable for customer leadership and compliance review: timeline, root cause, impact, resolution, preventive actions
Maintain audit-ready case documentation in Salesforce Service Cloud throughout
File actionable bug reports Engineering can act on without follow-up
Surface recurring patterns as structured insights to Product and ML teams
Flag compliance-adjacent issues immediately: call recording, disclosure language, member data