Requirements
Qualifications (Education & Experience)Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related discipline.A master's degree in a relevant field is an advantage.3–7 years of experience in software development, data science, or AI/ML engineering.Proven experience working with Oracle Database (SQL, PL/SQL, performance tuning, views, materialized views) is a plus.Experience with MCP (Model Context Protocol), CrewAI, LlamaIndex, Kafka, Redis, Kubernetes, and Azure OpenAI.Experience delivering AI solutions for Finance, Supply Chain, Sales, HR, or Customer Service.Strong programming skills in Python (preferred) and familiarity with R, Java, or similar languages.Hands-on experience with ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).Solid understanding of data modelling, relational databases, and performance optimization.Experience building and deploying RESTful APIs or microservices (e.g., Flask, FastAPI, .NET, or Java frameworks).Familiarity with cloud platforms (OCI, Azure, AWS, or GCP) for AI workloads is an advantage.Knowledge of CI/CD, Git, and DevOps practices for AI/M
Description
1.Job SummaryWe are looking for an AI transformation lead to design, develop, and deploy AI and analytics solutions using enterprise data extracted from Oracle Fusion Cloud and Oracle Databases.The role focuses on transforming Oracle business data into predictive models, insights, and decision-support tools that add real business value across Finance, HR, Sales, and Operations.The vacancy will be offshore based in favor of Samir Group - KSA2.Key Responsibilities:Solution Design and DevelopmentDesign, implement, and maintain AI/ML models (e.g., forecasting, classification, recommendation, NLP) using enterprise data sourced from Oracle Fusion and Oracle DB.Develop robust data pipelines to extract, transform, and load (ETL) data from Oracle Fusion Cloud (ERP, HCM, SCM, CX, Finance) and on-premise/cloud Oracle Databases into AI platforms and analytics environments.Build APIs, microservices, or other service layers to expose AI models to internal systems, portals, and mobile applications.Data and Model ManagementPerform data preparation, cleansing, and feature engineering to ensure high-quality input for AI models.Evaluate, tune, and retrain models to improve accuracy, performance, and stability.Implement monitoring, logging, and version control for models, datasets, and code.Collaboration and GovernanceWork closely with business stakeholders (Finance, HR, Sales, Operations, etc.) to translate business problems into AI use cases and technical specifications.Collaborate with DBAs, Oracle functional consultants, and integration teams to ensure end-to-end alignment of AI solutions with existing architecture.Ensure adherence to information security, data privacy, and regulatory requirements in all AI solutions.Documentation and SupportPrepare comprehensive technical documentation, including design documents, data dictionaries, and deployment guides.Provide knowledge transfer to operations and support teams and assist in incident analysis related to AI components.