Interview Mode : Weekend Walkin drive (Face to Face )
Interview Date : 19-Sep-26(Saturday )
Note : Only candidates currently located in should a Chennai apply.
Role : Azure AI/ML Engineer
Experience : 5 to 10 Years
Location : Chennai
Must-Have
- 5–8 years of experience in software engineering or AI/ML development, with at least 4+ years working with Azure AI services.
- Strong hands-on experience with Python for backend development, AI pipelines, and LLM integrations.
- Strong hands-on experience with Azure AI Document Intelligence including extraction, forms, OCR, and classification.
- Deep understanding of Azure OpenAI, including GPT models, embeddings, chat completions, prompt engineering, and content safety.
- Practical experience using Azure AI Foundry for building, testing, and operationalizing AI apps.
- Experience building AI solutions in cloud-native Azure environments including:
- Azure Functions
- Azure API Management (APIM)
- Azure Resource Groups
- Azure Storage Accounts
- App Insights
- Azure App Service
- Azure Key Vault
- Hands-on experience making calls to LLM APIs (chat completions, embeddings, model inference endpoints) and integrating them into applications.
- Experience architecting and implementing RAG systems using Azure Cognitive Search or vector index stores.
- Strong programming experience in Python or C# (Node.js acceptable) for backend microservices and integrations.
- Practical experience with Azure services including Logic Apps, Event Grid, Storage, Functions, and automated workflows.
- Solid knowledge of Responsible AI, privacy, compliance, and secure deployment models.
- Strong debugging and optimization skills for AI workloads (cost, latency, throughput).
- Hands-on experience with Azure DevOps, Git repositories, CI/CD pipelines, IaC, and deployment automation.
- Strong analytical, communication, and stakeholder management skills.
Desirable Skills / Knowledge / Experience
- Experience using vector databases such as Azure Cosmos DB with vector indexing, Redis Enterprise, or Pinecone.
- Familiarity with multi-agent AI architectures, orchestration frameworks, and agentic workflows.
- Exposure to Power Platform AI Builder and low-code AI integrations.
- Understanding of NLP techniques including entity extraction, embeddings, semantic search, text analytics, and conversation design.
- Experience with frameworks like LangChain, Semantic Kernel, or LlamaIndex.