Support Engineer (24x7 Operations Support)

Role: Support Engineer (24x7 Operations Support)

Location: Bengaluru

Experience: 3-4 years

Role Overview

About the Role

We are building a dedicated 24x7 support team for the Visiogen platform — a suite of business-critical applications including HiApp (Human Intelligence App), our primary business application and the core platform Optometrists (ODs) use to monitor and respond to patient conversations across multiple clinics; Customer Portal; Operations Portal; and clinic chatbot integrations — all deployed on Zeiss's Azure infrastructure. As a Support Engineer, you will be a Forward Deployed Engineer: hands-on, embedded close to the business, and directly responsible for keeping these systems running and resolving issues that are often unique to individual clinics, customers, or integrations.

WHAT MATTERS MOST

We are hiring for problem-solvers first. This role is for someone who has demonstrably rolled up their sleeves and solved messy, customer-specific, or one-off production issues — not just someone who has followed runbooks. Relevant certifications (Azure, Kubernetes, etc.) are a plus, but proven, hands-on troubleshooting experience carries far more weight than a certificate.

Key Responsibilities

Platform Monitoring

1. Monitor application health, availability, and performance across HiApp, Customer Portal, and Operations Portal
2. Monitor Azure infrastructure and services, integrations, and APIs using Log Analytics and Application Insights
3. Review logs, dashboards, and alerts to catch potential issues before they impact customers

Incident Management

1. Respond to production incidents as part of a 24x7 rotation and classify them by severity (P1/P2/P3)
2. Own incidents through to resolution, coordinating with engineering teams during outages
3. Restore services within agreed SLA timelines and provide clear, timely status updates

Troubleshooting & Root Cause Analysis

1. Investigate application failures across React, .NET, and Python (Gen AI) services
2. Diagnose Azure resource issues — AKS pod crashes, App Gateway/WAF issues, PostgreSQL and Redis problems, Function App failures
3. Analyze API, database, network, and integration issues, and perform root cause analysis with corrective recommendations
4. Troubleshoot clinic-specific chatbot integration failures, including JavaScript embed issues on customer websites

Business & Operations Support

1. Support new clinic onboarding activities, including data ingestion via Function Apps into the vector database
2. Assist the Operations and Customer Success teams with product-level troubleshooting
3. Handle customer-specific or customized requirements that fall outside standard playbooks, and drive them to resolution independently

Required Skills & Experience

Area

What We're Looking For

Cloud & Infrastructure

Hands-on experience with Azure Kubernetes Service (AKS), Application Gateway (WAF_v2), Private Endpoints, Traffic Manager, and general Azure resource management

Data Layer

Working knowledge of PostgreSQL and Redis — able to troubleshoot connectivity, performance, and query-level issues

Serverless / Compute

Experience with Azure Function Apps (EP1 / Elastic Premium plans) and data ingestion pipelines feeding a vector database

CI/CD & Release

Familiarity with Azure DevOps, CI/CD pipelines, ACR (Premium), release validation, and deployment support

Application Stack

Ability to troubleshoot across React frontends, .NET backend services, and Python-based Gen AI services

Monitoring & Diagnostics

Proficiency with Log Analytics, Application Insights, and Key Vault-based secrets/configuration troubleshooting

Problem-Solving

Proven track record of resolving customer-specific or one-off production issues under time pressure, not just textbook scenarios

Soft Skills

Clear incident communication, ownership mindset, comfort working night/weekend shifts as part of a 24x7 rotation

Preferred Qualifications

1. Prior experience as a Forward Deployed Engineer, Solutions Engineer, or Production/L2-L3 Support Engineer in a customer-facing or embedded support model
2. Experience supporting healthcare, clinic, or patient-facing platforms is a plus, not a requirement
3. Azure or Kubernetes certifications are valued but secondary to demonstrated troubleshooting experience
4. Exposure to Gen AI / vector database concepts (e.g., embeddings, ingestion pipelines) is a plus

What Success Looks Like

1. Incidents are triaged accurately and communicated clearly within SLA
2. Customer- and clinic-specific issues are resolved with minimal escalation, using sound judgment rather than rigid scripts
3. Recurring issues are identified and root-caused, reducing repeat incidents over time
4. New clinics are onboarded smoothly with minimal friction on data ingestion and chatbot integration