GEN AI Backend Engineer

Job Description:

Key Responsibilities:

• Backend Development: Design develop and maintain serverside logic ensuring high performance and responsiveness of applications.
• Generative AI Integration: Collaborate with the AI research team to integrate cuttingedge Generative AI models into the backend infrastructure.
• API Development: Build robust APIs to support the frontend team thirdparty services and mobile applications.
• Data Management: Develop and manage databases ensuring efficient data storage retrieval and security for AI models and applications.
• Scalability: Optimize backend architecture for scalability to handle large volumes of data and requests especially in AIrelated workloads.
• Security: Implement best practices in securing backend systems and ensuring data privacy especially in AI model handling and deployment.
• Collaboration: Work closely with frontend developers AI researchers and product managers to deliver highquality AIdriven products.
• Performance Monitoring: Continuously monitor the performance of backend services identify bottlenecks and implement optimizations.

Required Qualifications:

• Educational Background: Bachelor s or Master s degree in Computer Science Engineering or a related field.
• Experience: 3 years of experience in backend development with a focus on AIdriven applications.

• Proficiency in backend languages such as Python Node.js or Java.
• Experience with frameworks like Django Flask or Express.
• Strong understanding of RESTful API design and development.
• Experience with databases like PostgreSQL MongoDB or MySQL.
• Handson experience with cloud services (AWS Azure GCP) and containerization (Docker Kubernetes).
• Knowledge of Generative AI models (e.g. GPT DALLE) and experience in deploying them in production environments

Preferred Qualifications:

• Experience with AI/ML frameworks such as TensorFlow PyTorch or Keras.
• Familiarity with version control systems (e.g. Git) and CI/CD pipelines.
• Previous experience working in agile development environments.
• Understanding of data privacy regulations and AI ethics.

How to Apply:

database management,aws,api development,flask,communication skills,restful api design,ai model optimization techniques,node.js,gcp,analytical skills,express,keras,neural networks,kubernetes,artificial intelligence,generative ai models,ci/cd pipelines,dall-e,java,backend development,postgresql,mongodb,django,git,security,tensorflow,communication,python,machine learning principles,mysql,containerization,microservices architecture,problem-solving skills,framework,docker,ai ethics,gpt,pytorch,data privacy regulations,cloud services,agile development environments,azure,devops practices