AI Integration Developer

🧬 Hiring: AI Integration Specialist (Healthcare & Genomics / AWS / RAG / .NET) Location: On-site Bahrain Experience: Minimum 3years Contract Duration: 2-Year Full-Time Contract Candidate should be available locally in Bahrain About the Role: We are looking for an experienced AI Integration Specialist to lead the deployment of machine learning models, Pharmacogenomics predictions, conversational chatbots, and vector search systems for a large-scale national genomic dataset. Key Responsibilities: • Build, fine-tune, and deploy ML/DL models (Classification, Regression, Clustering) using TensorFlow, PyTorch, and Scikit-learn. • Implement production-grade RAG architectures, vector databases (Pinecone, FAISS, Weaviate), and LLM integrations (GPT, Claude). • Architect cloud-native AI pipelines utilizing AWS SageMaker, AWS NextFlow, AWS Bedrock, Lambda, S3, and IAM. • Design RESTful APIs and integrate backend services within .NET/ASP.NET Core enterprise environments. • Clean, normalize, and process large structured/unstructured healthcare and genomic datasets. • Requirements & Qualifications: • Education: Bachelor’s degree in information technology, Computer Science, Artificial Intelligence, or a related field • Core Technologies: TensorFlow, PyTorch, Python, Scikit-learn, AWS Ecosystem (SageMaker, Bedrock, NextFlow), Vector DBs. • Integration Capabilities: ASP.NET Core, RESTful APIs, Microservices, SQL/NoSQL, Git, Docker, MLOps. • Domain Knowledge: Experience with healthcare, genomics, or large-scale clinical dataset workflows is highly preferred. • Strong communication skills to articulate AI solutions to both technical and non-technical stakeholders. 📩 How to Apply: Send your updated CV directly to [email protected] keep the subject AI Integration Developer or whatsapp at +97338024430 apply below! Show more Show less

Bachelor’s degree in information technology, Computer Science, Artificial Intelligence, or a related field; Core Technologies: TensorFlow, PyTorch, Python, Scikit-learn, AWS Ecosystem (SageMaker, Bedrock, NextFlow), Vector DBs; Integration Capabilities: ASP.NET Core, RESTful APIs, Microservices, SQL/NoSQL, Git, Docker, MLOps; Domain Knowledge: Experience with healthcare, genomics, or large-scale clinical dataset workflows is highly preferred.

Build, fine-tune, and deploy ML/DL models (Classification, Regression, Clustering) using TensorFlow, PyTorch, and Scikit-learn. Implement production-grade RAG architectures, vector databases (Pinecone, FAISS, Weaviate), and LLM integrations (GPT, Claude). Architect cloud-native AI pipelines utilizing AWS SageMaker, AWS NextFlow, AWS Bedrock, Lambda, S3, and IAM. Design RESTful APIs and integrate backend services within .NET/ASP.NET Core enterprise environments. Clean, normalize, and process large structured/unstructured healthcare and genomic datasets.