Azure AI Engineer

Tata Consultancy Services Limited; Bengaluru; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Tata Consultancy Services Limited is seeking an experienced AI/ML engineer to design and deploy Azure-based AI solutions. You will build LLM-driven apps, implement prompt and context engineering, and operationalize document processing pipelines across enterprise systems.

The role requires 4+ years in software or AI/ML, strong backend skills (Python or C#), and hands-on experience with Azure OpenAI, Azure Functions, and Cognitve Search.

Qualifications

• 4+ years in software engineering or AI/ML development.
• Hands-on with Azure AI services and LLMs.
• Strong Python or C# backend experience.
• Experience building and deploying AI pipelines and integrations.
• Familiarity with RAG, vector stores, and semantic search.
• Proficient in prompt engineering and grounding strategies.
• Knowledge of security, privacy, and compliance in AI systems.
• Ability to collaborate with stakeholders and document solutions.

Responsibilities

• Design, develop, and deploy AI solutions using Azure AI Document Intelligence, Azure OpenAI, and Azure AI Foundry.
• Build and operationalize LLM-based apps with prompt/context engineering and embeddings.
• Create intelligent document processing pipelines (classification, extraction, OCR).
• Implement RAG architectures using cognitive search or vector stores for grounding and citing results.
• Integrate AI capabilities with enterprise systems via REST APIs, Azure Functions, APIM, or Logic Apps.
• Develop cloud-native AI services with Azure resources and storage.
• Maintain clean, secure Python or C# code following best practices.
• Ensure security, governance, and compliant deployment of AI workloads.
• Monitor model performance, optimize latency/cost, and troubleshoot issues.
• Collaborate with stakeholders to define architectures and measurable outcomes.
• Produce technical runbooks and knowledge base content.
• Stay current with Azure AI capabilities and enterprise tooling.

Skills

AI/ML development

Azure AI services

Python

LLM integrations

RAG architectures

Prompt engineering

Security & compliance

Stakeholder communication

Cloud architecture

Data pipelines

Tools

Azure Functions

Azure OpenAI

Azure Cognitive Search

LangChain

LlamaIndex

Redis Enterprise

Pinecone

Azure Cosmos DB (vector)

REST APIs

Git/Azure DevOps

Job description

• 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.
• 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.
• 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.

Responsibilities or Expectations from the Role:

• 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.