Support Analyst

• About the Role:

The Tier 3 Support Engineer acts as the highest technical escalation point between our customer-facing teams and the R&D department. This role is designed for a technical "detective" who can perform deep-dive investigations into complex issues involving AI note generation, audio processing, and cloud infrastructure. You will be part of a dedicated technical squad (3-4 engineers) ensuring the stability of our clinical tools during US peak hours.

• Technical Requirements:

-English: Advanced

-A technical person overall with QA mindset to be able to isolate client issue

-
Strong troubleshooting
skills with a methodical approach to troubleshooting "edge case" bugs in a fast-paced startup environment.

-Ability to debug
REST APIs
using
Postman
and inspect network traffic/DOM issues via Chrome DevTools.

-Proficiency with
Datadog or Grafana
for analyzing metrics and system alerts. Experience with tracing application flows in
Kibana, Sentry
, or similar log aggregation tools.

-
Basic SQL
proficiency for data investigation (joining tables, filtering session records).

-Basic skills in
Python or Bash
for troubleshooting automation is a big advantage.

-Ability to understand complex architectures involving Kafka events, Django backends, and React frontends.

-Strong communication skills with an excellent English (written and verbal) for high-stakes internal and external coordination.

-Ability to quickly master new AI-driven features and health-tech compliance standards.

• Job Responsibilities:

-Serve as the final technical escalation point for issues that Tier 1 and 2 teams cannot resolve.

-Commitment to maintaining coverage during critical US business hours. (ET timezone).

-Build and maintain a strong understanding of product and architecture.

-Perform root cause analysis on complex product failures, identifying if issues are localized, cloud-based, or AI-related.

-Reproduce reported bugs in staging environments and provide detailed technical handovers to the Dev and QA teams.

-Monitor system health and performance using real-time dashboards to identify widespread service degradations.

-Execute SQL queries to verify data integrity and trace session lifecycles.

-Use scripting to automate log parsing or repetitive troubleshooting tasks.

-Maintain clear communication with both technical R&D teams and non-technical customer success managers.

• Department/Project Description:

We are redefining the standard of care in mental health. Our platform empowers clinicians by automating administrative burdens—such as note-taking and compliance auditing—using cutting-edge AI and real-time audio analysis. By bridging the gap between clinical sessions and actionable data, we allow providers to focus on what matters most: the patient.

It uses a Chrome extension to capture session data and scrape information from clinical interfaces, which is then processed through a Django backend and Flask-based AI microservices. The system handles real-time data orchestration via Kafka and complex batch workflows with Airflow. Security and identity are managed via Auth0 and Cloudflare WAF. You will investigate technical issues across this entire stack, including browser-level scraping failures, API errors, and event-driven processing delays.