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.

- 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