Description

Key Responsibilities

Collaborate with technical leads and product owners to understand requirements and refine user stories.

Design, develop, test, and deploy scalable AI and software solutions.

Build RESTful APIs using FastAPI and GraphQL APIs using Strawberry.

Develop real-time data pipelines using Kafka or Azure Event Hubs.

Design and integrate applications with databases such as PostgreSQL and MongoDB.

Develop scalable data-processing solutions using Apache Spark and Delta Lake.

Build and support collaborative data engineering and machine-learning workflows using Databricks.

Integrate LLM/Generative AI APIs into enterprise applications.

Design and implement cloud-native solutions using Microsoft Azure.

Deploy and manage applications using Docker and Kubernetes.

Develop and maintain CI/CD pipelines using Azure DevOps or GitHub Actions.

Troubleshoot technical issues, optimize application performance, and promote engineering best practices.

Collaborate with engineers across different experience levels and technical disciplines.

Required Qualifications

Strong professional experience developing applications with Python and modern web frameworks.

Hands-on experience with FastAPI and GraphQL/Strawberry.

Experience developing and integrating RESTful APIs and understanding API architecture principles.

Experience with Kafka or Azure Event Hubs and real-time streaming data pipelines.

Strong database experience with PostgreSQL, MongoDB, or similar technologies.

Experience with Spark, Delta Lake, and distributed data processing.

Hands-on experience with Azure Databricks.

Experience integrating OpenAI, Llama, or other mainstream LLM/GenAI APIs.

Strong understanding of Microsoft Azure cloud architecture, scalability, and distributed systems.

Experience with Docker and Kubernetes.

Experience building CI/CD pipelines using Azure DevOps or GitHub Actions

Key Skills

Education

Bachelor’s degree