GenAI Engineer

2 days ago

Toronto, Ontario, Canada BULL-IT SOLUTIONS LTD Full time

Key Responsibilities


• Design and implement Generative AI solutions leveraging modern architectures and cloud-native services.


• Develop and optimize Retrieval-Augmented Generation (RAG) patterns, including data indexing and chunking strategies.


• Build and maintain data pipelines for large-scale data processing using Azure services such as Databricks, Data Factory, and Storage Accounts.


• Implement CI/CD pipelines for AI applications, ensuring automated testing and streamlined deployment.


• Architect and develop microservice-based solutions for GenAI workloads.


• Collaborate with cross-functional teams to integrate AI models into enterprise systems.


• Monitor and optimize model performance (accuracy, latency, throughput) and ensure scalability for production workloads.


• Maintain compliance with security and governance standards in cloud environments.

________________________________________

Preferred Skillset


• Generative AI Expertise: Strong understanding of generative AI models, algorithms, and their business applications. Hands-on experience with RAG optimization.


• Data Engineering: Proven experience in building scalable data pipelines and working with large, complex datasets.


• Cloud & Azure Proficiency: Deep knowledge of Azure services (Databricks, Data Factory, Storage Accounts) and full-stack Azure development.


• Programming Skills: Proficiency in Python and SQL for data processing and model integration.


• Microservice Architecture: Experience in designing and deploying microservice-based solutions.


• Release Management: Familiarity with CI/CD pipelines for AI applications.


• Platform Experience: Knowledge of LLM deployment in cloud environments and performance optimization.


• Collaboration & Communication: Ability to work effectively with multi-functional teams and stakeholders.


• Adaptability: Comfortable handling changes and delivering results in complex, dynamic environments.

________________________________________

Nice-to-Have


• Experience with model monitoring tools and setting up performance metrics dashboards.


• Familiarity with Azure AI services, ML Ops frameworks, and containerization (Docker/Kubernetes).


• Exposure to data governance and security best practices in cloud environments.

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