AI Engineer in Banking Domain

We have an urgent requirement for AI Engineer in Banking Domain (Must) is required for our banking client in Oman • Design, develop, deploy, and maintain AI, Machine Learning, Deep Learning, and Generative AI solutions, including predictive models, NLP, recommendation engines, and intelligent automation applications.-Must • Build data pipelines, integrate AI models with enterprise applications, APIs, and cloud platforms (Azure, AWS, GCP), while supporting MLOps, CI/CD, and production deployment.--Must • Collaborate with business stakeholders to identify AI opportunities, translate business requirements into AI-driven solutions, and support the bank’s digital transformation, innovation, and customer experience initiatives.---Must • Ensure AI solutions comply with data governance, cybersecurity, regulatory, and Responsible AI standards, including model monitoring, bias detection, explainability, documentation, version control, and audit readiness.--Must • Experience developing and deploying AI/ML solutions, predictive models and Generative AI applications.--MustBanking Must Summary • Responsible for designing, developing, implementing and maintaining Artificial Intelligence and Machine Learning solutions that support the bank’s digital transformation strategy. The role builds intelligent applications, develops predictive models, automates business processes and integrates AI capabilities into enterprise systems to enhance operational efficiency, customer experience and data-driven decision-making while ensuring compliance with governance, cybersecurity and regulatory requirements.ResponsibilitiesStrategic • Design and implement AI solutions aligned with the bank’s digital transformation and innovation strategy. • Identify opportunities to leverage AI, Generative AI, Machine Learning, and automation to improve business processes and customer experience. • Support the development of the bank’s AI roadmap, standards, and best practices. • Collaborate with business stakeholders to understand business challenges and translate them into AI-driven solutions. • Evaluate emerging AI technologies, frameworks, and industry trends to recommend innovative solutions. Operational • Build and optimize predictive models, recommendation engines, natural language processing, computer vision, and Generative AI applications where applicable. • Design, develop, test, deploy, and maintain AI and Machine Learning models for business use cases. • Develop data pipelines and integrate AI models with enterprise applications, APIs and cloud platforms. • Monitor AI model performance, accuracy, and reliability, implementing improvements as needed. • Develop technical documentation, model documentation and user guides. • Work closely with Data Engineers, Business Analysts, Solution Architects and IT teams to deploy AI solutions into production. • Troubleshoot AI applications and provide technical support for deployed solutions. • Participate in proof-of-concepts, pilots, and innovation initiatives. Compliance • Maintain proper documentation, version control, and audit trails for AI models and development activities. • Ensure AI solutions comply with the bank’s data governance policies, cybersecurity standards, responsible AI principles, and regulatory requirements. • Ensure secure handling of sensitive customer and business data during model development and deployment. • Monitor AI models for bias, fairness, accuracy, explainability, and ongoing performance. Skills • Python, SQL, and AI programming frameworks • Machine Learning and Deep Learning • Generative AI and Large Language Models • API development and system integration • Natural Language Processing • Cloud platforms (Azure, AWS, or Google Cloud) • Data Engineering and model deployment (MLOps) • Git, CI/CD, and DevOps practices • Data Visualization and Reporting tools • Agile Development methodologies Education • Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Information Technology, or a related discipline. • A Master’s degree in Artificial Intelligence, Machine Learning, Data Science, or a related field is an advantage. • Professional certifications in Microsoft Azure AI, AWS Machine Learning, Google Professional Machine Learning Engineer, TensorFlow, or equivalent AI technologies are preferred. Experiences • 3-6 years of experience in Artificial Intelligence, Machine Learning, Data Science or Software Engineering. • Experience developing and deploying AI/ML solutions, predictive models and Generative AI applications. • Proficiency in Python and modern AI frameworks, with experience integrating AI solutions into enterprise applications. Skills: artificial intelligence,bank,machine learning

Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Information Technology, or a related discipline. A Master’s degree in Artificial Intelligence, Machine Learning, Data Science, or a related field is an advantage. Professional certifications in Microsoft Azure AI, AWS Machine Learning, Google Professional Machine Learning Engineer, TensorFlow, or equivalent AI technologies are preferred. 3-6 years of experience in Artificial Intelligence, Machine Learning, Data Science or Software Engineering. Experience developing and deploying AI/ML solutions, predictive models and Generative AI applications. Proficiency in Python and modern AI frameworks, with experience integrating AI solutions into enterprise applications.

Design, develop, deploy, and maintain AI, Machine Learning, Deep Learning, and Generative AI solutions, including predictive models, NLP, recommendation engines, and intelligent automation applications. Build data pipelines, integrate AI models with enterprise applications, APIs, and cloud platforms (Azure, AWS, GCP), while supporting MLOps, CI/CD, and production deployment. Collaborate with business stakeholders to identify AI opportunities, translate business requirements into AI-driven solutions, and support the bank’s digital transformation, innovation, and customer experience initiatives. Ensure AI solutions comply with data governance, cybersecurity, regulatory, and Responsible AI standards, including model monitoring, bias detection, explainability, documentation, version control, and audit readiness. Experience developing and deploying AI/ML solutions, predictive models and Generative AI applications.