? HIRING | AI Engineer – Azure Cloud | 4–5 Years | Pune (Onsite)

We are looking for a skilled AI Engineer with strong hands-on experience in Artificial Intelligence, Generative AI, Machine Learning, LLMs, and Python development.

The ideal candidate should have practical experience designing, developing, integrating, and deploying AI-powered applications, with Microsoft Azure as the primary cloud platform for AI development and deployment.

Candidates should have a valuable understanding of AI engineering, LLM-based applications, RAG architectures, AI agents, prompt engineering, and cloud-based AI solutions.

? Job Details

- Position: AI Engineer – Azure Cloud
- Experience: 4–5 Years
- Location: Pune
- Work Mode: Work From Office (Onsite)
- Employment Type: Full-Time
- Notice Period: Immediate Joiners / Serving Notice Period up to 15 Days Preferred

? Key Responsibilities 1. AI & Generative AI Development

- Design, develop, and implement AI-powered applications using Python and modern AI frameworks.
- Build Generative AI solutions using LLMs such as GPT and other foundation models.
- Develop prompt engineering strategies and optimize LLM responses.
- Implement Retrieval-Augmented Generation (RAG) solutions for enterprise applications.
- Develop AI agents and multi-agent workflows for business use cases.
- Integrate LLMs with enterprise applications, databases, and external APIs.

2. Machine Learning & AI Engineering

- Develop, train, test, and deploy machine learning models.
- Work with supervised and unsupervised learning techniques.
- Perform data preprocessing, feature engineering, model evaluation, and optimization.
- Implement NLP solutions, text processing, and semantic search capabilities.
- Evaluate AI model performance, accuracy, and reliability.

3. Microsoft Azure Cloud & AI Services





- Develop and deploy AI/ML applications using Microsoft Azure.
- Work with Azure OpenAI Service and Azure AI Foundry.
- Use Azure Machine Learning for model development, deployment, and monitoring.
- Work with Azure AI Search for vector search, semantic search, and RAG implementations.
- Deploy AI applications using Azure App Services, Azure Functions, and Azure Container Apps.
- Integrate Azure Storage, databases, and other cloud services into AI workflows.
- Implement secure access using Azure Key Vault and Managed Identities.

4. AI Frameworks & Application Development

- Work with Python frameworks such as FastAPI and Flask.
- Use LangChain, LangGraph, LlamaIndex, or Semantic Kernel.
- Develop REST APIs and integrate AI models into applications.
- Work with vector databases such as FAISS, ChromaDB, Pinecone, or Azure AI Search.
- Implement embeddings, vector indexing, and similarity search.

5. Model Deployment & LLMOps

- Deploy and manage AI/ML models on Azure cloud infrastructure.
- Implement model versioning, prompt versioning, and evaluation workflows.
- Build CI/CD pipelines using Azure DevOps or GitHub Actions.
- Monitor model performance, latency, token consumption, and application costs.
- Optimize AI applications for scalability, performance, and reliability.
- Work with Docker and containerization for application deployment.

? Mandatory Technical Skills
- Python Programming
- Artificial Intelligence / Machine Learning




- Generative AI and Large Language Models (LLMs)
- Azure OpenAI Service
- Microsoft Azure Cloud
- Retrieval-Augmented Generation (RAG)
- Prompt Engineering
- LangChain / LangGraph / LlamaIndex / Semantic Kernel
- Machine Learning Model Development and Deployment
- NLP and Embeddings
- Vector Databases / Vector Search
- REST API Development and Integration
- Azure AI Foundry / Azure Machine Learning
- Azure AI Search
- Model Deployment and Monitoring

? Good-to-Have Skills
- AI Agents and Multi-Agent Systems
- Model Context Protocol (MCP)
- Fine-tuning and evaluation of LLMs
- PyTorch / TensorFlow / Scikit-learn
- FastAPI / Flask
- Docker / Kubernetes
- Azure Functions / App Services
- Azure DevOps / GitHub Actions
- Terraform / Bicep
- Azure Monitor / Application Insights
- LLMOps and MLOps

? Candidate Profile
- 4–5 years of relevant experience in AI/ML or AI Engineering.
- Strong hands-on Python programming and AI application development experience.
- Practical experience developing Generative AI and LLM-based applications.
- Experience implementing RAG pipelines and integrating LLMs with enterprise data.
- Hands-on experience using Microsoft Azure for AI development and deployment.
- Understanding of cloud architecture, application integration, and security.
- Strong analytical, debugging, and problem-solving skills.
- Ability to collaborate with engineering teams and technical stakeholders.

We are looking for hands-on AI Engineers who can build, integrate, and deploy production-ready AI solutions on Microsoft Azure!

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📌 AI Engineer – Azure Cloud (Pune)
🏢 Philodesign Technologies
📍 Pune