Azure AI/ML Engineer 19th September 26 Walkin Chennai

TCS has been a great pioneer in feeding the fire of young techies like you. We are a global leader in the technology arena and theres nothing that can stop us from growing together.

What we are looking for

Role: Azure AI/ML Engineer

Experience Range: 5 to 10 Years

Location: Chennai

Interview Date: 19th September 26 (09:00 AM to 12:00 PM)

Interview Venue: Gate 04, TCS Siruseri Campus,Plot No. 1, G‑1, SIPCOT Information Technology Park

Near Siruseri Special Economic Zone (SEZ), Navalur Post, Siruseri, Chennai – 603103, Tamil Nadu

Note-While coming for Walkin:-

· Please carry 2 or more copies of updated resume, 2 Passport size photo along with Govt ID proof(Xerox 2 copies)

· Please do not bring personal laptop or electronic gadgets to TCS premises.

Must Have:

• 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.

Good to Have:

• 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.

Certifications such as:

• Azure AI Engineer Associate (AI-102)
• Azure Fundamentals(AZ-900)

Essential

• Design, develop, and deploy AI solutions using Azure AI Document Intelligence, Azure OpenAI, and Azure AI Foundry.
• Build and operationalize LLM‑based applications, including prompt engineering, context engineering, embeddings, chat completions, and grounding strategies.
• Develop intelligent document processing pipelines using Azure AI Doc Intelligence for document classification, extraction, OCR, and automated workflows.
• Implement RAG architectures using Azure Cognitive Search or vector databases for retrieval grounding, chunking, ranking, and citation‑based responses.
• Integrate LLM and AI capabilities with enterprise systems using REST APIs, Azure Functions, APIM, Logic Apps, or Power Platform.
• Build cloud-native AI services using Azure Functions, Azure Resource Groups, App Services, Storage Accounts, App Insights, and Key Vault.
• Develop and maintain clean, secure, and well-tested Python or C# code following engineering best practices.
• Ensure adherence to security, governance, and compliance standards including encryption, responsible AI, and regulated-industry policies.
• Monitor AI model performance and system behavior, optimize response quality, troubleshoot issues, and reduce operational bottlenecks.
• Collaborate with stakeholders to identify use cases, define architectures, and deliver measurable AI outcomes.
• Produce solution documents, system diagrams, runbooks, and technical knowledge-base content.
• Stay current with emerging Azure AI ecosystem capabilities, LLM advancements, and enterprise AI tooling.

Minimum Qualification:

• 15 years of full-time education
• Minimum percentile of 50% in 10th, 12th, UG & PG (if applicable)