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

Dear Candidate,

If you or someone you know is interested in this opportunity, please submit your CV directly to [HIDDEN TEXT] (this method is preferred due to the high volume of applications, which may cause some CVs to be overlooked).

It is important to note that visa sponsorship is currently unavailable.

Main Responsibilities

• Evaluate business and technical requirements, converting them into data flows, integration frameworks, and implementation strategies.
• Design and execute dependable data movement between upstream and downstream enterprise systems utilizing REST APIs, SFTP, file transfers, and batch processing.
• Establish data contracts, interfaces, mappings, and transformation needs across various systems and teams.
• Create scripts, applications, and APIs for data extraction, transformation, and integration across different systems.
• Facilitate integrations across enterprise data platforms and data lake environments.
• Ensure the accurate transformation, mapping, aggregation, and delivery of data to target systems, implementing necessary data quality and reconciliation controls.
• Assist with GenAI use cases by preparing and integrating both structured and unstructured data for document ingestion, enrichment, search, and RAG workflows.
• Diagnose integration and data movement challenges across development, testing, and production environments.
• Collaborate closely with application, data platform, infrastructure, and security teams to provide comprehensive solutions.
• Critique inefficient or inadequate designs and recommend effective, scalable, and sustainable solutions.
• Assist with SIT, UAT, and production rollouts, ensuring integration reliability, error management, and monitoring.
• Clearly document system flows, data mappings, interfaces, and integration methodologies.
• Provide production support, including incident investigation, troubleshooting, bug resolution, code adjustments, and application enhancements.
• Troubleshoot across the full technology stack, including Python, Celery, databases, Docker, Kubernetes/OpenShift, and CI/CD processes.
• Implement technical upgrades and continuous improvements based on production challenges and operational needs.

Essential Qualifications

• 5-10 years of experience in system analysis, integration engineering, data engineering, or roles focused on technical delivery.
• Proficient in Python and SQL for data management, scripting, automation, and troubleshooting.
• Solid understanding of frontend technologies, including HTML and Jinja templating.
• Practical experience with Celery for asynchronous/background task management.
• Strong capability to translate requirements into system flows, data flows, interface specifications, and implementation strategies.
• Hands-on experience with REST APIs, SFTP, batch processing, file-based integration, and data pipeline orchestration.
• Strong grasp of data mapping, transformation, aggregation, reconciliation, and data quality measures.
• Experience collaborating with upstream and downstream teams to achieve enterprise integrations.
• Familiarity with Java and enterprise data platforms such as Cloudera.
• Hands-on experience with Git, including branching, pull requests, code reviews, and controlled release methodologies.
• Knowledge of CI/CD, Jira, Confluence, and enterprise deployment processes.
• Experience in deploying and supporting applications on Kubernetes and OpenShift (OCP).
• Experience with Control-M or similar scheduling software.
• Familiarity with logging and monitoring tools like Splunk and Elastic Stack.
• Exposure to GenAI concepts, including document ingestion, RAG, embeddings, and data preparation for AI workflows.
• Excellent communication and stakeholder management skills, capable of working across business, application, data, infrastructure, and security teams.
• Strong systems-thinking and problem-solving abilities, adept at navigating complex enterprise settings and challenging suboptimal designs.