AI engineer in digital payments

Ready to move beyond experiments and build AI that performs in the real world? We’re looking for an AI Engineer to design, develop and bring intelligent solutions into production—from large language models (LLMs) and agentic frameworks to predictive algorithms.

• Design AI from end to end: build autonomous edge AI architectures connecting cloud services and payment platforms, with security, availability and resilience built in.
• Build the data foundations: use Azure Data Factory and Azure Databricks to ingest, transform and curate structured and unstructured payment data for model training and real-time inference.
• Turn generative AI into useful products: develop LLM-powered and agentic solutions for customer assistance, anomaly explanation and documentation generation.
• Apply machine learning to payments: use supervised, unsupervised and reinforcement learning to develop predictive and prescriptive capabilities for risk management, fraud detection and transaction optimisation.
• Engineer for production: build Jenkins CI/CD workflows for automated testing, deployment and monitoring across hybrid infrastructure; optimise edge inference for low latency and high throughput.
• Prove and monitor performance: run experiments, historical-data backtesting and A/B evaluations to assess fraud reduction, customer satisfaction and process efficiency.
• Implement logging and observability to identify model drift, data-quality issues and operational incidents.
• Build responsibly: partner with payments experts, product managers, data, cybersecurity and compliance teams to translate business requirements into scalable solutions, embedding encryption, access controls, privacy, explainability and auditability.
• Strengthen the team: document architectures, data models, pipelines and operational processes; mentor colleagues in Azure Databricks, Azure Data Factory, Jenkins and AI engineering practices.
• Keep improving: evaluate emerging generative AI, edge inference and MLOps approaches, recommending practical enhancements that improve resilience, business value and trust in digital payments.

• Strong hands-on experience designing, developing and operating production-grade AI and ML solutions, with a focus on reliability, scalability, observability and maintainability.
• Extensive experience with Azure Databricks and Azure Data Factory, spanning large-scale data engineering, model development and production operations.
• Practical proficiency in Jenkins for CI/CD pipelines, automated testing and safe, repeatable releases across hybrid environments.
• A deep understanding of feature engineering, model selection, hyperparameter tuning and evaluation metrics, applied to payments risk and fraud use cases.
• Proven experience building generative AI applications, including conversational agents or content-generation tools integrated with payment platforms, with attention to accuracy, explainability and responsible data use.
• Solid payments-domain knowledge, including transaction flows, settlement, chargebacks, fraud patterns and regulatory considerations.
• Clear communication and structured documentation skills, with experience collaborating across distributed teams and hybrid environments during day-shift operations.

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