Technical Support Engineer - L2

interface.ai; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Benefits offered by this job

Comprehensive benefits

Job summary

interface.ai is seeking an experienced Advanced Technical Support professional to own escalations end-to-end, debug across REST APIs, webhooks, and core banking connectors, and lead incident response for enterprise clients in the financial services sector.

You will analyze AI conversations, refine AI behavior, and contribute to knowledge base improvements while collaborating with Engineering, Product, and Compliance teams in a remote-first setup.

Qualifications

• 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.
• Familiarity with Kubernetes: pod logs, deployment states, cluster context during incident investigation.
• AI & Tooling: configuring agents, chaining tools, debugging multi-step workflows.
• Proficient with Cursor and Claude Code for investigations, codebase exploration, and scripting.
• Communication & Agency: clear written and verbal communication with both technical and non-technical stakeholders.
• Audit-ready documentation: every case readable by someone not in the conversation.
• High Agency: drive issues to resolution independently.

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, 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 specificity for ML/Product to act on, and close the feedback loop.
• Write, refine, and retire knowledge base articles to 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 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 for Engineering, surface recurring patterns to Product/ML teams.
• Flag compliance-adjacent issues immediately: call recording, disclosure language, member data.

Skills

Technical support

REST API debugging

PostgreSQL

Python scripting

Observability tools

Kubernetes basics

Salesforce Service Cloud

AI tooling

Communication

Root cause analysis

Tools

OpenSearch

Kibana

Grafana

Datadog

Salesforce Service Cloud

Cursor

Claude Code

API traces

Job description

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

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
• 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

• 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, 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

Why Join Us

Remote-first

• High ownership
• AI innovation at the frontier of financial services

Comprehensive benefits