Aadhith Krishna R profile photo 1 on Tal

Aadhith Krishna R

Technical Support

Chennai

2+ years of work experience

M2P Fintech
Mar 20251 yr 1 moMar 2026

India

Owned end-to-end resolution of product issues, ensuring timely acknowledgment and SLA adherence across cloud platforms. Migrated multiple PostgreSQL databases across engine versions to AWS RDS using automated Bash scripting, ensuring minimal downtime and version compatibility during transitions. Worked cross-functionally with Engineering and Ops teams by diagnosing root causes, implementing workarounds, and escalating with structured documentation. Acted as the primary communication bridge between clients and internal teams throughout the issue lifecycle. Drove process improvement through SOP creation, escalation playbooks, and KT sessions — reducing resolution time and enabling self-service for repeat issues. Owned end-to-end resolution of complex B2B technical incidents via voice, email, and chat for international enterprise clients across multiple time zones, maintaining >95% SLA adherence on a 24x7 rotating shift schedule. Reduced manual engineering intervention by 30% by building systematic API payload validation and webhook configuration debugging workflows, enabling Tier-1 resolution of issues previously escalated to engineering. Investigated and diagnosed integration failures, API errors, and edge-case processing issues by reproducing problems in test environments — delivering structured root cause documentation to engineering and product teams. Authored 15+ client-specific SOPs, FAQs, and technical runbooks that reduced average resolution time for repeat incident categories and accelerated onboarding for new support engineers. Conducted KT sessions on product integration flows, incident management protocols, and monitoring tool usage (Grafana, Prometheus), measurably improving team diagnostic capability.
Mad Street Den
May 20231 yr 11 mosMar 2025

Chennai, Tamil Nadu, India

Supported global enterprise clients across e-commerce, retail, healthcare, and BFSI sectors on the vue.ai SaaS platform, serving regions across EU, APAC, and the US. Triaged and resolved 20+ daily tickets involving system errors and configuration issues. Wrote SQL queries in Amazon Athena to filter and analyse production logs by timestamp and event type, enabling faster root cause identification during incident investigations. Debugged production environments using Kibana, CloudWatch, and Grafana to identify anomalies and reduce downtime. Investigated and escalated issues with structured root cause documentation to Engineering and Product teams, working closely with developers to verify fixes before production rollout. Managed 1000+ monthly alerts via Opsgenie across AWS, Azure, and GCP environments. Led knowledge base and documentation improvements, standardising troubleshooting playbooks and reducing repeat queries through self-service content.
Mad Street Den
May 20234 mosAug 2023

Chennai, Tamil Nadu, India

GitHub
@Aadhithkrishna-star

Aadhith’s AI Stack

antigravity
antigravity
langgraph
langgraph
ChatGPT
ChatGPT

Education

BE, Electrical and Electronics Engineering

Muthyammal College of Engineering

20154 yrs2019

AWS re/Start Program Learner at Amazon Web Services (AWS), Cloud Computing

AWS restart

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Aadhith Krishna R on Tal

Headline

Technical Support

About

- I hold a bachelor's degree in the stream of Electrical and Electronics Engineering from Muthayammal College of Engineering. - I had successfully acquired the certification on AWS CCP by gaining required theoritical and hands-on knowldge. - Practicing Data Science and Machine Learning for over 8 months, Completed 600+ hours of coursework, 12 coding assignments, and 2 projects (Web scraping, Exploratory data analysis) - Currently, I am working as a Product Support Engineer at Mad Street Den

Location

Chennai

AI stack

antigravity

langgraph

ChatGPT

Work experience

Associate Engineer at M2P Fintech, Mar 2025 - Mar 2026 · 1 yr 1 mo, India, Owned end-to-end resolution of product issues, ensuring timely acknowledgment and SLA adherence across cloud platforms. Migrated multiple PostgreSQL databases across engine versions to AWS RDS using automated Bash scripting, ensuring minimal downtime and version compatibility during transitions. Worked cross-functionally with Engineering and Ops teams by diagnosing root causes, implementing workarounds, and escalating with structured documentation. Acted as the primary communication bridge between clients and internal teams throughout the issue lifecycle. Drove process improvement through SOP creation, escalation playbooks, and KT sessions — reducing resolution time and enabling self-service for repeat issues. Owned end-to-end resolution of complex B2B technical incidents via voice, email, and chat for international enterprise clients across multiple time zones, maintaining >95% SLA adherence on a 24x7 rotating shift schedule. Reduced manual engineering intervention by 30% by building systematic API payload validation and webhook configuration debugging workflows, enabling Tier-1 resolution of issues previously escalated to engineering. Investigated and diagnosed integration failures, API errors, and edge-case processing issues by reproducing problems in test environments — delivering structured root cause documentation to engineering and product teams. Authored 15+ client-specific SOPs, FAQs, and technical runbooks that reduced average resolution time for repeat incident categories and accelerated onboarding for new support engineers. Conducted KT sessions on product integration flows, incident management protocols, and monitoring tool usage (Grafana, Prometheus), measurably improving team diagnostic capability.

Technical Product Support Specialist at Mad Street Den, May 2023 - Mar 2025 · 1 yr 11 mos, Chennai, Tamil Nadu, India, Supported global enterprise clients across e-commerce, retail, healthcare, and BFSI sectors on the vue.ai SaaS platform, serving regions across EU, APAC, and the US. Triaged and resolved 20+ daily tickets involving system errors and configuration issues. Wrote SQL queries in Amazon Athena to filter and analyse production logs by timestamp and event type, enabling faster root cause identification during incident investigations. Debugged production environments using Kibana, CloudWatch, and Grafana to identify anomalies and reduce downtime. Investigated and escalated issues with structured root cause documentation to Engineering and Product teams, working closely with developers to verify fixes before production rollout. Managed 1000+ monthly alerts via Opsgenie across AWS, Azure, and GCP environments. Led knowledge base and documentation improvements, standardising troubleshooting playbooks and reducing repeat queries through self-service content.

Technical Product Support at Mad Street Den, May 2023 - Aug 2023 · 4 mos, Chennai, Tamil Nadu, India

Education

BE, Electrical and Electronics Engineering, Muthyammal College of Engineering

AWS re/Start Program Learner at Amazon Web Services (AWS), Cloud Computing, AWS restart

Public links

github: https://github.com/Aadhithkrishna-star