Technical Support Engineer - L2 at interface.ai (Bengaluru, India)Technical Support Engineer - L2

𝗔𝗯𝗼𝘂𝘁 𝗜𝗻𝘁𝗲𝗿𝗳𝗮𝗰𝗲.𝗮𝗶

Interface.ai builds Generative AI-powered virtual assistants for banks and credit unions - automating customer service across voice and chat for 100+ financial institutions. Our proprietary AI achieves 90%+ accuracy on Day 1.

𝗔𝗯𝗼𝘂𝘁 𝘁𝗵𝗲 𝗥𝗼𝗹𝗲

𝗥𝗼𝘁𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗦𝗵𝗶𝗳𝘁𝘀 Our AI agents handle the majority of member interactions autonomously. What reaches L2 is technically complex, compliance-sensitive, or business-critical. You own escalations end-to-end, drive AI quality improvement through every case you close, and serve as a trusted technical partner to customers that have zero tolerance for ambiguity.

𝗪𝗵𝗮𝘁 𝗬𝗼𝘂'𝗹𝗹 𝗗𝗼

𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗦𝘂𝗽𝗽𝗼𝗿𝘁

• 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 AI Agent Quality & Improvement
• 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 Incident & Customer Management
• 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 Feedback & Process Improvement
• 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

𝗪𝗵𝗮𝘁 𝗬𝗼𝘂'𝗹𝗹 𝗕𝗿𝗶𝗻𝗴

Technical

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

𝗔𝗜 & 𝗧𝗼𝗼𝗹𝗶𝗻𝗴

• 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 Communication & Agency
• 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