Azure DevOps Engineer

Wissen Technology • Python • 1 month ago
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Salary
≈ $18k – $80k per year (Estimated)
Location
In office (Bengaluru)
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Wissen Technology

Wissen is a global technology consulting and software engineering firm specializing in digital transformation and custom software development. Founded in 2000, the company delivers end-to-end technology solutions across key sectors, including banking and financial services, healthcare, telecommunications, and retail. Its core offerings span application modernization, cloud architecture, artificial intelligence and machine learning, big data analytics, DevOps, and quality assurance.
wissen.com • HQ: Bengaluru, India • Information Technology • IT Consulting • Est. 2015

Requirements:

  • Strong hands-on experience in Microsoft Azure Cloud.
  • Good understanding of Azure services such as Compute, Storage, Event Hub, Event Subscription, Storage Queue, and PaaS services.
  • Basic understanding of Azure AI Foundry and AI-related Azure service setup.
  • Good Azure networking basics: VNet, subnet, routing, and basic troubleshooting.
  • Strong knowledge of Terraform, especially: Terraform state, plan/apply, troubleshooting failures, migration risks, Terraform Enterprise concepts
  • Strong Python coding capability, not just basic scripting.
  • Experience using Python for API integration, automation, JSON/YAML handling, and internal tooling.
  • Good understanding of CI/CD pipelines.
  • Ability to troubleshoot pipeline failures.
  • Comfortable with YAML and JSON.
  • Ability to troubleshoot Azure infrastructure/platform issues.
  • Ability to collect logs/evidence and coordinate with network/app/Microsoft support teams.
  • Basic awareness of agentic AI / LLM concepts.
  • Awareness of security and cost best practices.

Good to Have Skills:

  • Hands-on experience withHarness.
  • Hands-on experience with Terraform Enterprise.
  • Exposure to LangGraph / LangChain.
  • Exposure to agentic AI workflows or skill creation.
  • Exposure toClaude or enterprise LLM integrations.
  • Knowledge ofAzure ML Workspace, model registry, and managed endpoints.
  • MLOps / LLMOps knowledge.
  • FinOps / Azure cost optimisation experience.
  • Azure certifications: AZ-104 AZ-305 AZ-400 AZ-500
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