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interface.ai

AI-driven virtual assistants for banking

Technical Support Engineer

Customer SupportConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listed

About the Job

Requirements

  • Have 5 or more years of technical or implementation support experience at a B2B software-as-a-service company.
  • Debug REST APIs and webhooks, including authentication failures, integration traces, and event-driven architecture.
  • Use PostgreSQL and SQL to query session data, analyze usage patterns, and validate data integrity across integrated systems.
  • Write Python diagnostic scripts, parse logs, and create lightweight internal tools.
  • Use observability platforms such as OpenSearch, Kibana, Grafana, or Datadog, including queries, dashboards, and distributed traces.
  • Have voice-channel familiarity, including Session Initiation Protocol and interactive voice response routing, and distinguish automatic speech recognition errors from AI model errors.
  • Use Salesforce Service Cloud or a similar platform for case management, escalation tracking, and audit-trail documentation.
  • Create and orchestrate AI agents by configuring agents, chaining tools, defining guardrails, and debugging multi-step workflows.
  • Use Cursor and Claude Code for investigations, codebase exploration, and scripting.
  • Critically evaluate AI conversation transcripts across voice and digital channels.
  • Communicate clearly in writing and verbally with technical and non-technical customer stakeholders.
  • Produce precise, audit-ready documentation that allows someone who was not part of a conversation to understand the case.
  • Drive issues to resolution independently, make judgment calls, and take ownership of outcomes from intake through closure.
  • Manage an independent case queue without supervision.

Responsibilities

  • 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 hallucinations, intent misclassification, knowledge coverage, flow misconfiguration, and integration issues.
  • Debug issues using logs, call recordings, digital transcripts, API traces, and observability tooling.
  • Analyze escalated AI conversations, categorize root causes with enough specificity for Machine Learning and Product teams to act on, and close the feedback loop.
  • Write, refine, and retire knowledge-base articles to continuously increase 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 in a timely manner.
  • Lead P1/P2 incident response, coordinating war rooms, providing timestamped updates, and managing parallel stakeholders across Engineering and customer teams.
  • Write post-mortems for customer leadership and compliance review, including the timeline, root cause, impact, resolution, and preventive actions.
  • Maintain audit-ready case documentation in Salesforce Service Cloud.
  • File actionable bug reports that Engineering can act on without follow-up.
  • Surface recurring patterns as structured insights to Product and Machine Learning teams.
  • Immediately flag compliance-adjacent issues involving call recording, disclosure language, and member data.

Desired Qualifications

  • Familiarity with Kubernetes, including reading pod logs, understanding deployment states, and navigating cluster context during incident investigations.

About the Company

interface.ai

AI-driven virtual assistants for banking

Interface.ai provides an AI-powered platform that delivers intelligent virtual assistants for banks and credit unions, available across voice, chat, and mobile. The system is pre-trained on over 60 banking-specific use cases and integrates with core banking, CRM, and LOS systems, featuring Agentic Voice AI, Agentic Chat AI, and Agentic Employee AI, with device biometrics and real-time monitoring for security. It differentiates itself by serving community banks and credit unions with outโ€‘ofโ€‘theโ€‘box banking AI and end-to-end automation across channels, using a performance-based pricing model. Its goal is to improve operational efficiency, boost customer self-service, and help financial institutions scale AI-powered service.

Company size
51-200
Company stage
Early VC
Total funding
$80M
Headquarters
San Francisco, CA
Founded
2018

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