About the Role / About the Job
We are currently looking for an AI Integration Developer for our Bahrain operations. This position involves working with advanced AI technologies and requires a robust set of skills and experiences in various areas of AI model development and integration.
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Responsibilities
- Develop and implement AI models using Supervised & Unsupervised Learning, including Model Training, Validation, and Evaluation, as well as Feature Engineering and Optimization.
- Work with various types of AI models such as Classification, Regression, and Clustering, while focusing on model performance tuning and monitoring.
- Gain practical knowledge and experience with Large Language Models (LLMs) such as GPT and Claude.
- Apply expertise in Prompt Engineering, Retrieval-Augmented Generation (RAG), and Vector databases, including but not limited to Pinecone, FAISS, and Weaviate.
- Build conversational AI systems and chatbots, in addition to developing document processing systems.
- Utilize frameworks such as TensorFlow, PyTorch, and Scikit-learn to create effective AI solutions.
- Develop RESTful APIs for integrating AI models with enterprise applications.
- Manage and analyze large datasets, specifically within Healthcare and Genomics data contexts.
- Use AWS tools such as SageMaker, NextFlow, Bedrock, Lambda, and S3 to enhance AI model deployment and management.
- Design cloud-based AI architectures, including the deployment, monitoring, and scaling of AI models in a production environment.
- Understand and implement data preprocessing pipelines for both structured and unstructured data.
- Be familiar with Microservices architecture, API-first design methodologies, SQL and NoSQL databases, and version control systems like Git.
- Utilize Microsoft .NET technologies including ASP.NET Core, Blazor/MVC, Web APIs, and Entity Framework for backend service design and development.
- Develop and maintain backend services and API integrations within .NET-based applications, ensuring they align with .NET application architecture and database integrations.
- Apply authentication/security concepts in cloud-based deployment environments.
- Employ strong problem-solving and analytical thinking abilities to tackle challenges.
- Communicate technical and AI concepts clearly to non-technical stakeholders.
- Document effectively and collaborate well within a team-oriented environment.
- Experience with MLOps practices, containerization (Docker), and CI/CD pipelines.
- Exposure to healthcare, licensing, or insurance domain systems is advantageous.
- Prepare technical documentation, architecture diagrams, and solution designs.
- Work within structured project environments, similar to government or RFP frameworks.
- Support production systems and critical deployments, and provide operational assistance as needed.
Experience Required
- Strong understanding of AI modeling techniques and valuable hands-on experience in AI integration and deployment.
