Python & Azure AI Developer (Backend)- (Immediate joiner)

Role & responsibilities

Work mode :

Experience :

Budget :

Mandates :

Checklist

Have you built backend systems using Django Framework?

Have you built end-to-end AI/ML solutions?

Have you deployed the AI/ML pipelines in Azure cloud?

Do you have hands-on experience in PostgreSQL Database?

Do you have experience in AKS(Azure Kubernetes Service)

Preferred candidate profile

Position Summary

• We are seeking a skilled Python/Django Developer with deep expertise in Azure AI services. In this role, you will architect and implement backend systems, integrate AI/ML pipelines, and leverage OpenAI/Conversational AI capabilities to build scalable, production-ready solutions. You will contribute across the full development lifecyclecollaborating with product managers, data scientists, and frontend engineerswhile enforcing best practices in security, performance, and data privacy.

Key Responsibilities

• Backend Development (Python & Django)

• Design, build, and maintain robust RESTful APIs and web services using Python and Django or Django REST Framework.
• Model and optimize PostgreSQL schemas and queries for high performance under production workloads.
• Write clean, well-documented code; implement unit, integration, and performance tests; participate in code reviews.

• Azure AI Service Integration

• Architect and deploy end-to-end AI/ML pipelines using Azure Machine Learning and Azure Cognitive Services (Vision, Speech, Language).
• Containerize and deploy trained ML models in Azure Kubernetes Service (AKS) or Azure Container Instances; monitor health, performance, and scalability.
• Implement automated CI/CD for model retraining, validation, and redeployment.

• Open AI LLM & Conversational AI

• Integrate Azure OpenAI Service and OpenAI APIs (e.g., ChatGPT, GPT-4, text embeddings) to enable functionality like summarization, Q&A, and conversational agents.
• Develop prompt-engineering standards, monitor token usage and cost, and fine-tune custom models (where applicable) for domain-specific needs.
• Build middleware that orchestrates AI calls, handles error/fallback logic, and ensures data privacy when routing requests to OpenAI endpoints.

• Full Lifecycle Delivery

• Lead requirement gathering, architectural design, and sprint planning within an Agile/Scrum framework.
• Continuously monitor, troubleshoot, and optimize both application code and deployed AI/ML models in production environments.
• Produce and maintain comprehensive documentation: API specifications, data flow diagrams, model versioning logs, and runbooks.

• Collaboration & Best Practices

• Partner closely with product managers to align technical solutions with business goals.