GenAI Engineer

Responsibilities

• Design, develop, and implement GenAI solutions that integrate with Azure and AWS platforms.
• Collaborate with cross-functional teams to gather requirements and define project objectives.
• Conduct research and stay up-to-date with the latest advancements in GenAI, Azure, OpenAI, AWS, and Google GenAI technologies.
• Develop and maintain scalable and efficient codebase for GenAI applications.
• Optimize GenAI models and algorithms for performance and accuracy.
• Troubleshoot and debug GenAI applications, ensuring smooth operation and minimal downtime.
• Collaborate with data scientists and machine learning engineers to enhance GenAI capabilities.
• Provide technical guidance and mentorship to junior team members.
• Stay informed about industry trends and best practices in GenAI engineering and cloud service integration.

Requirements

• Bachelor's or master's degree in computer science, Engineering, or a related field.
• Proven experience as a GenAI Engineer, with a focus on Azure and OpenAI integration.
• Experience with AWS and Azure GenAI services is preferred.
• Strong programming skills in languages such as Python and/or Java.
• Experience with Azure services, including Azure WebApp services, Azure AI Services, and Azure Functions.
• Experience with Large Language model integration with APIs, building AI agents and working with multi-modal models.
• Understanding of machine learning algorithms and deep learning frameworks.
• Proficiency in data preprocessing, feature engineering, and model evaluation techniques.
• Strong problem-solving and analytical skills.
• Excellent communication and collaboration abilities.
• Ability to work independently and as part of a team in a fast-paced environment.
• Experience with AWS services, such as Amazon ECS, Fargate, Lambda, Dynamo DB, Bedrock etc.
• Good to have knowledge of Google Cloud services, including Google Cloud AI Platform, Google Cloud Functions, and Google Cloud AutoML.
• Experience with cloud-based deployment and scaling of GenAI applications on Azure, AWS, and Google Cloud.
• Knowledge of containerization technologies such as Docker and Kubernetes.
• Familiarity with DevOps practices and tools for CI/CD pipelines.
• Contributions to open-source GenAI or cloud service integration projects.