Flawless InterviewsFlawless InterviewsScript Solutions W.L.L
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Job Description We are looking for an experienced AI Integration Developer to design, develop, integrate, deploy, and support Artificial Intelligence and Machine Learning solutions within enterprise and healthcare-related systems. The developer will work on machine learning models, Large Language Models, RAG solutions, conversational AI, document-processing systems, AI APIs, cloud-based AI services, and enterprise application integrations. The role also requires familiarity with Microsoft .NET technologies to support integration between AI solutions and existing enterprise applications. Key Responsibilities -Design, develop, train, evaluate, and optimize machine learning models. -Work with supervised and unsupervised learning techniques. -Develop classification, regression, and clustering models. -Perform feature engineering and model performance optimization. -Develop and integrate solutions using Large Language Models such as GPT, Claude, or equivalent models. -Design and implement Retrieval-Augmented Generation solutions. -Develop prompt-engineering strategies for enterprise AI applications. -Work with vector databases such as Pinecone, FAISS, and Weaviate. -Build conversational AI solutions, chatbots, intelligent assistants, and document-processing systems. -Develop AI and machine-learning solutions using TensorFlow, PyTorch, and Scikit-learn. -Develop RESTful APIs to integrate AI models with enterprise applications. -Work with structured and unstructured datasets. -Process and analyze large datasets, including healthcare and genomics-related data. -Design data preprocessing, transformation, and cleaning pipelines. -Develop and deploy AI solutions using AWS cloud services. -Work with AWS SageMaker, Bedrock, Lambda, Nextflow, S3, and IAM. -Deploy, monitor, scale, and maintain AI models in production. -Implement MLOps practices for model lifecycle management and monitoring. -Develop containerized applications using Docker. -Support CI/CD pipelines and automated deployment processes. -Design scalable cloud-based AI architectures. -Integrate AI solutions with .NET applications. -Support ASP.NET Core, Blazor, MVC, Web API, and Entity Framework integrations. -Prepare AI architecture diagrams, integration designs, API documentation, and technical documentation. -Support production systems, incident resolution, critical deployments, and operational activities.
-Strong practical experience in Artificial Intelligence and Machine Learning. -Strong understanding of supervised and unsupervised learning techniques. -Experience with classification, regression, and clustering models. -Experience in model training, validation, evaluation, tuning, and monitoring. -Practical experience with LLMs such as GPT, Claude, or similar platforms. -Strong understanding of prompt engineering. -Hands-on experience implementing RAG solutions. -Experience with vector databases such as Pinecone, FAISS, or Weaviate. -Experience developing conversational AI, chatbots, or document-processing solutions. -Strong experience with TensorFlow, PyTorch, and/or Scikit-learn. -Strong Python development skills. -Experience developing RESTful APIs. -Experience handling large structured and unstructured datasets. -Experience with data preprocessing and transformation pipelines. -Hands-on experience with AWS services including SageMaker, Bedrock, Lambda, S3, Nextflow, and IAM. -Experience deploying and monitoring AI models in production. -Strong knowledge of Docker, MLOps, and CI/CD practices. -Familiarity with microservices and API-first architecture. -Knowledge of SQL and NoSQL databases. -Experience using Git and version-control systems. -Good understanding of Microsoft .NET technologies. -Familiarity with ASP.NET Core, Blazor/MVC, Web APIs, and Entity Framework. -Understanding of application security, authentication, and authorization. -Strong problem-solving and analytical skills. -Ability to clearly explain AI concepts to technical and non-technical stakeholders. -Strong technical documentation and communication skills. -Exposure to healthcare, genomics, licensing, insurance, or government systems is preferred. -Ability to work within structured enterprise or government project environments. -Willingness to support production systems and critical deployments. -Ability to work 40 hours per week, Sunday to Thursday, from 7:00 AM to 3:00 PM. -Willingness to provide 24/7 on-call support for urgent incidents when required.