Project Description:
• Designed and developed an enterprise-grade Generative AI platform using Python, FastAPI, and FastMCP to automate recruitment workflows and provide intelligent candidate insights. Built scalable, production-ready APIs that integrated with OpenAI GPT and Anthropic Claude models for candidate screening, resume analysis, job matching, and automated recruiter assistance.
• Implemented RAG (Retrieval-Augmented Generation) pipelines using vector databases such as Pinecone/Milvus to provide context-aware responses from enterprise knowledge repositories. Developed AI Agents and custom plugins/skills to automate candidate engagement, interview scheduling, talent recommendations, and workflow orchestration.
• Owned the complete application lifecycle, including architecture design, API development, deployment, monitoring, observability, logging, and performance optimization. Leveraged AI-assisted development tools such as Claude, Codex, and VS Code to accelerate development, debugging, code reviews, and delivery.
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Responsibilities:
• Design, develop, and maintain scalable, high-performance applications using Python, FastAPI, and FastMCP.
• Build and deploy production-grade REST APIs and AI-powered services following best practices for security, performance, and reliability.
• Develop and integrate Generative AI solutions using Large Language Models (LLMs) such as OpenAI GPT and Anthropic Claude.
• Design and implement AI Agents, Plugins, Skills, and MCP-based integrations to automate business workflows.
• Build and optimize RAG (Retrieval-Augmented Generation) pipelines using vector databases such as Pinecone or Milvus.




• Create prompt engineering frameworks and context-management strategies to improve LLM response quality.
• Develop end-to-end AI solutions covering architecture, implementation, testing, deployment, and production support.
• Collaborate with product managers, architects, and business stakeholders to translate requirements into technical solutions.
• Implement monitoring, logging, observability, and performance optimization for AI applications and APIs.
• Ensure code quality through unit testing, code reviews, CI/CD pipelines, and adherence to software engineering best practices.
• Evaluate and adopt emerging AI technologies, frameworks, and industry best practices.
• Leverage AI-assisted development tools such as Claude, Codex, and VS Code to accelerate development, debugging, and delivery.
• Troubleshoot complex technical issues and provide timely resolutions in production environments.
• Mentor team members and contribute to technical design discussions and innovation initiatives. Mandatory Skills Description:
• 7+ years of experience
• Microservices Development | Python | FastAPI (With Async Programming) | Any NoSQL DB | Azure (Basic Experience) | DevOps (Docker)|| Agents |
• LLM / GenAI
• API
• FastAPI
• Python
• Deployment: Docker Kubernetes GitHub Actions
• Azure: Cosmos DB, Redis (Cache), Azure AI Search
• GenAI: LLMs, OpenAI GPT, Claude
• Monitoring & Logging: Datadog Nice-to-Have Skills Description:
• Azure AI Search
• Microsoft Fabric
• Kafka
• Snowflake
• Terraform
• Docker / Kubernetes
• Microsoft Purview Languages:
• English: C1 Advanced

📌 Azure AI Data Engineer (India)
🏢 Luxoft
📍 India