AI Full Stack Engineer (Banking, 1-year renewable contract)

Dear Applicant,

If you or someone you know is interested, please send the CV directly to [Confidential Information] (most preferred, as I may overlook some CVs due to the high volume).

Please note that visa sponsorship is not available at this time.

Key Responsibilities

• Analyse business and technical requirements and translate them into data flows, integration designs and implementation plans.
• Design and implement reliable data movement across upstream and downstream enterprise systems using REST APIs, SFTP, file-based transfers and batch pipelines.
• Define data contracts, interfaces, mappings and transformation requirements across multiple systems and teams.
• Develop scripts, programs and APIs to extract, transform and integrate data from different systems.
• Coordinate integrations across enterprise data platforms and data lake environments.
• Ensure data is accurately transformed, mapped, aggregated and delivered to target systems with appropriate data quality and reconciliation controls.
• Support GenAI use cases by preparing and integrating structured and unstructured data for document ingestion, enrichment, search and RAG workflows.
• Troubleshoot integration and data movement issues across development, testing and production environments.
• Work closely with application, data platform, infrastructure and security teams to deliver end-to-end solutions.
• Challenge inefficient or unsuitable designs and propose practical, scalable and maintainable solutions.
• Support SIT, UAT and production deployments, ensuring integration reliability, error handling and monitoring.
• Document system flows, data mappings, interfaces and integration processes clearly.
• Provide production support, including incident investigation, troubleshooting, bug fixes, code corrections and application enhancements.
• Troubleshoot across the technology stack, including Python, Celery, databases, Docker, Kubernetes/OpenShift and CI/CD.
• Implement technical enhancements and continuous improvements arising from production issues and operational requirements.

Key Requirements

• 5-10 years of experience in system analysis, integration engineering, data engineering or technical delivery roles.
• Strong Python and SQL skills for data handling, scripting, automation and troubleshooting.
• Good understanding of frontend technologies such as HTML and Jinja templating.
• Hands-on experience with Celery for asynchronous/background task processing.
• Strong ability to translate requirements into system flows, data flows, interface specifications and implementation plans.
• Practical experience with REST APIs, SFTP, batch processing, file-based integration and data pipeline orchestration.
• Strong understanding of data mapping, transformation, aggregation, reconciliation and data quality controls.
• Experience working across upstream and downstream teams to deliver enterprise integrations.
• Exposure to Java and enterprise data platforms such as Cloudera.
• Hands-on experience with Git, branching, pull requests, code reviews and controlled release practices.
• Familiarity with CI/CD, Jira, Confluence and enterprise deployment processes.
• Experience deploying and supporting applications on Kubernetes and OpenShift (OCP).
• Experience with Control-M or equivalent scheduling tools.
• Familiarity with logging and monitoring tools such as Splunk and Elastic Stack.
• Exposure to GenAI concepts, including document ingestion, RAG, embeddings and data preparation for AI workflows.
• Strong communication and stakeholder management skills, with the ability to work across business, application, data, infrastructure and security teams.
• Strong system-thinking and problem-solving skills, with the ability to navigate complex enterprise environments and challenge weak designs.