Programming &

- Scripting Languages:

- Technologies: Python, Java, C++, or JavaScript/TypeScript.

- Application: Ability to read, comprehend, and navigate complex, enterprise-scale codebases to trace execution paths, understand implementation details, and pinpoint potential defects.

Authentication, Identity &

- Connector Tech:

- Technologies: OAuth 2.0, OpenID Connect (OIDC), JWT (JSON Web Tokens), SAML, HTTP/HTTPS protocols.

- Application: Deep expertise in debugging authentication and authorization flows, managing token lifecycles, and troubleshooting third-party SaaS connector integrations.

Database &

- Query Languages:

- Technologies: Google Cloud Spanner, Standard SQL (ANSI SQL), Relational Database Concepts.

- Application: Robust proficiency in writing and executing complex SQL queries, utilizing joins, subqueries, and aggregations to retrieve and correlate incident-related data from Spanner databases.

API &

- Distributed Systems Troubleshooting:

- Technologies: REST APIs, gRPC, JSON, Protocol Buffers (Protobufs), API testing tools (e.g., cURL, Postman), Distributed Tracing tools (e.g., Google Cloud Trace, Dapper).

- Application: Tracing API request flows across microservices and distributed architectures to identify service-to-service communication failures, timeouts, and latency issues.

Telemetry, Logging &

- Issue Tracking:

- Technologies:



Cloud Logging or similar log aggregation tools (e.g., Splunk, ELK), Regex for log filtering, Buganizer (or enterprise equivalents like Jira).

- Application: Querying, filtering, and interpreting high-volume logs from various sources to trace user journeys, alongside rigorous issue lifecycle management in ticketing systems.

Version Control &

- Code Search:

- Technologies: Git, Google Code Search (or similar semantic code search tools like Sourcegraph).

- Application: Efficiently navigating repositories to find relevant code snippets, track commit history, and understand system behaviors.

GCP &

- Google Internal Tools Experience:

- Prior experience utilizing Google Cloud Platform services, Google Admin, Google Spanner, Buganizer, and internal Code Search tools.

AI/LLM Familiarity:

- General understanding of Generative AI, Large Language Models (LLMs), and enterprise AI products to better contextualize customer issues within Gemini Enterprise.

Enterprise Support Background:

- Previous experience in Tier 3/Escalation Support, SRE, or Sustaining Engineering for enterprise-grade SaaS/PaaS products.

Security &

- Compliance:

- Familiarity with enterprise data access, privacy compliance (e.g., GDPR, HIPAA), and handling sensitive customer data securely during investigations.

📌 Gem Enterprise Engineer (Bug Support, 6 To 8 years, bangalore) (Bengaluru)
🏢 Tata Consultancy Services
📍 Bengaluru