Mindtickle
About this role
Mindtickle sells an AI powered revenue enablement platform used to train sales teams and support deal execution, and G2 ranks it first in sales onboarding and training. This is the second line technical support role behind that platform. You take customer issues that the first line could not solve and debug them across backend services, APIs, the data platform, UI behaviour and the AI features, owning each ticket end to end until it is resolved. A large part of the job is diagnosis: reading browser logs, HAR files and network traces, querying system data, and telling apart a model problem from a data, configuration or infrastructure problem. You also write Bash, Python and SQL to automate log extraction and health checks, and turn each solved case into runbooks and documentation. A reader asked for customer success and technical account roles by name, and at 1 to 3 years this is the most junior of them.
Who this is for
What the posting asks for: 1 to 3 years of L2 technical support experience with enterprise SaaS platforms in a customer facing role, AWS cloud preferred. Mindtickle also wants a track record handling technical issues in production while supporting distributed systems, experience supporting a multi tenant SaaS product including its integrations and configuration management, and hands on troubleshooting of AI powered features with the ability to separate model issues from data, configuration or system level failures. Knowledge of authentication and enterprise integrations is required, specifically SSO protocols such as SAML, OAuth 2.0 and OpenID Connect.
The real day to day, in three parts. Operational support: responding quickly to customer queries, providing workarounds while permanent fixes are built, owning tickets to SLA, acting as an escalation point, and working across Product, Engineering, Quality Engineering and DevOps to kill recurring issues. Technical investigation: reproducing and debugging problems across backend services, APIs, data flows, UI behaviour and AI components, capturing browser logs, HAR files and network traces, analysing AI decision paths and validating model outputs for drift or anomalies, and running structured impact and severity analysis before escalating. The named tooling is Zipy, Datadog, SumoLogic, FullStory, Mixpanel and Metabase. Knowledge work: building runbooks, playbooks and troubleshooting guides, converting solved issues into product and documentation improvements, and running deep dive sessions and post incident walkthroughs. Automation: writing Bash, Python and SQL to automate log extraction, data analysis and issue replication, and contributing to AI assisted troubleshooting tooling.
Location and setup: Pune, Maharashtra. The posting does not state office days.
Honest fit guidance: this is support engineering, not product engineering, so you will be measured on resolution and SLA rather than shipped features. In exchange you get real depth in distributed systems debugging and unusually direct access to Engineering and Product. Mindtickle itself frames it as an L2 role with more influence than most. Good fit if you enjoy diagnosis and customer contact, poor fit if you want to be writing product code most of the week. The posting does not publish an interview process.
The real day to day, in three parts. Operational support: responding quickly to customer queries, providing workarounds while permanent fixes are built, owning tickets to SLA, acting as an escalation point, and working across Product, Engineering, Quality Engineering and DevOps to kill recurring issues. Technical investigation: reproducing and debugging problems across backend services, APIs, data flows, UI behaviour and AI components, capturing browser logs, HAR files and network traces, analysing AI decision paths and validating model outputs for drift or anomalies, and running structured impact and severity analysis before escalating. The named tooling is Zipy, Datadog, SumoLogic, FullStory, Mixpanel and Metabase. Knowledge work: building runbooks, playbooks and troubleshooting guides, converting solved issues into product and documentation improvements, and running deep dive sessions and post incident walkthroughs. Automation: writing Bash, Python and SQL to automate log extraction, data analysis and issue replication, and contributing to AI assisted troubleshooting tooling.
Location and setup: Pune, Maharashtra. The posting does not state office days.
Honest fit guidance: this is support engineering, not product engineering, so you will be measured on resolution and SLA rather than shipped features. In exchange you get real depth in distributed systems debugging and unusually direct access to Engineering and Product. Mindtickle itself frames it as an L2 role with more influence than most. Good fit if you enjoy diagnosis and customer contact, poor fit if you want to be writing product code most of the week. The posting does not publish an interview process.
Apply on company site
Opens jobs.lever.co, the employer's own application page. Applying is always free.