AI Full Stack Engineer – Integration & GenAI

OPTIMUM SOLUTIONS (SINGAPORE) PTE LTD; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

OPTIMUM SOLUTIONS (SINGAPORE) PTE LTD is seeking an AI Full Stack Engineer – Integration & GenAI to translate complex requirements into end-to-end system designs. You will build REST APIs, SFTP interfaces, and data pipelines across enterprise platforms, Data Lake, and downstream applications.

You will develop Python scripts and backend services for data extraction, transformation, validation, and automation, while supporting GenAI use cases with AI-ready data pipelines.

Qualifications

• 3+ years in System Analysis/Integration Engineering/Data Engineering/Full Stack Engineering/Technical Delivery.
• Strong hands-on Python and SQL development, data handling and automation.
• Experience with REST APIs, SFTP, batch processes, and file-based interfaces.
• Knowledge of enterprise data flows, data quality, mapping and transformation.
• Exposure to GenAI concepts including document ingestion and AI-enabled workflows.
• Experience with Docker, Kubernetes/OpenShift, CI/CD, Git, and Bash.

Responsibilities

• Analyze requirements and translate into end-to-end system, data flow, and integrations.
• Design and develop REST APIs, SFTP and batch interfaces across systems.
• Develop Python scripts and backend services for data extraction, transformation and integration.
• Build data pipelines across Data Lake and downstream apps.
• Perform data mapping, transformation, aggregation, reconciliation, and quality checks.
• Support GenAI use cases through data preparation and AI-ready pipelines.
• Develop components using Python, SQL, Celery, HTML, Jinja, and TypeScript.
• Support SIT/UAT, deployments, incident resolution and enhancements.
• Collaborate with business, data, infra, security, and architecture teams.

Skills

Python

SQL

REST APIs

SFTP

Batch processing

Data mapping

GenAI concepts

Jinja

TypeScript

HTML

Docker

Kubernetes

CI/CD

Git

Bash

Education

Bachelor's degree

Tools

Informatica

Cloudera

Jenkins

Job description

AI Full Stack Engineer – Integration & GenAI

Responsibilities

1. Analyze business and technical requirements and translate them into end-to-end system, data flow, and integration designs.
2. Design and develop REST APIs, SFTP, file-based interfaces, and batch integrations across upstream and downstream enterprise systems.
3. Develop Python scripts and backend services for data extraction, transformation, validation, automation, and system integration.
4. Design and implement reliable data pipelines and data movement across enterprise platforms, Data Lake, and downstream applications.
5. Perform data mapping, transformation, aggregation, reconciliation, and data quality validation to ensure accurate data delivery.
6. Support GenAI and RAG use cases through document ingestion, data preparation, enrichment, transformation, and AI-ready data pipelines.
7. Develop and maintain application components using Python, SQL, Celery, HTML, Jinja, and TypeScript.
8. Support SIT, UAT, deployment, production troubleshooting, incident resolution, and application enhancements.
9. Work with Docker, Kubernetes/OpenShift, CI/CD, Git, Jenkins, Control-M, and monitoring tools to ensure reliable application delivery.
10. Collaborate with business, application, data, infrastructure, security, and architecture teams to resolve issues and deliver scalable solutions.

Requirements

1. Minimum of 3 years relevant experience in System Analysis, Integration Engineering, Data Engineering, Full Stack Engineering, or Technical Delivery roles.
2. Strong hands-on experience in Python and SQL for development, data handling, automation, integration, and troubleshooting.
3. Practical experience developing and integrating REST APIs, SFTP, batch processes, and file-based interfaces.
4. Strong understanding of data mapping, transformation, aggregation, reconciliation, data quality, and enterprise data flows.
5. Experience with enterprise data platforms such as Informatica, Cloudera, Data Lake, or similar technologies.
6. Good knowledge of Celery, Docker, Kubernetes/OpenShift, CI/CD, Git, Jenkins, and Bash.
7. Working knowledge of HTML, Jinja, and TypeScript with exposure to application/UI development.
8. Experience supporting SIT/UAT, production deployments, incident management, debugging, and application enhancements.
9. Exposure to GenAI concepts including document ingestion, RAG, embeddings, data preparation, and AI-enabled workflows; ML model development is not mandatory.
10. Strong stakeholder management skills, with the ability to understand complex enterprise ecosystems.