Enterprise Analytics – Machine Learning Ops/AI Projects (VP1)

WhiteCrow Research; Kuala Lumpur; On-site; MYR 240,000 - 420,000; Full time

Job summary

WhiteCrow Research is seeking an Enterprise Analytics – Machine Learning Ops/AI Projects leader to architect, deploy, and operate AI/ML pipelines across cloud and on-prem environments. You will own DevOps pipelines, integrate AI models into production, and collaborate with cross-functional teams to ensure secure, scalable systems.

You have deep Linux, Python, OpenShift, Docker, Kubernetes experience, and a strong background in CI/CD, cloud platforms (AWS), and AI security.

Qualifications

• Bachelor’s degree in Computer Science or engineering.
• Bash/Unix/Linux command line toolkit.
• CI/CD pipelines: Bitbucket, Jenkins, Artifactory, Sonar, Veracode for SAST, JIRA workflow, and Confluence.
• OpenShift, Docker, Kubernetes.
• Cloud platforms (AWS).
• Exposure to data and network security and compliance in AI systems.
• API integration and microservices architecture.
• Python for automation and ML tasks.
• Workflow orchestrator (Ctrl-M).
• Logging/Monitoring tools: Splunk, Geneos.
• Observability: Langfuse, Elastic Stack, Grafana, OpenTelemetry.
• Generative AI concepts (prompt engineering, RAG pipelines) and Agentic AI.

Responsibilities

• Develop automation scripts using Linux shell scripting, Python, or other tools.
• Develop and maintain the entire DevOps pipelines.
• Ensure seamless deployment and integration between cloud/prem environments (AWS).
• Integrate AI models into production environments using containerized platforms such as OpenShift.
• Implement and maintain network security protocols to safeguard AI systems and data pipelines.
• Collaborate with cross-functional teams to translate AI workflows into robust engineering solutions.
• Monitor and optimize system performance, reliability, and scalability.
• Support CI/CD processes and infrastructure for AI model deployment and updates.

Skills

Linux scripting

Python

CI/CD pipelines

OpenShift

Docker

Kubernetes

AWS

AI security

Collaboration

Monitoring

API integration

Education

Bachelor’s degree in Computer Science or engineering

Tools

OpenShift

Docker

Kubernetes

AWS

Bitbucket

Jenkins

Artifactory

SonarQube

Veracode

JIRA

Confluence

Splunk

Langfuse

Elastic Stack

Grafana

OpenTelemetry

Ctrl-M

Job description

We are global talent research, insight, and sourcing specialists with offices in the UK, USA, Singapore, Malaysia, Hong Kong, Dubai, and India. Our international reach has helped us to understand and penetrate specialist markets at a global level. In addition to this, our service is also extended to complement our client’s in-house talent acquisition teams.

About our client

Our Client operates in the Financial Services Industry, with its headquarters rooted strongly in Singapore. It has its branches spread to more than 15 countries, providing employment to more than 25,000 people all over the world. They fall in the Forbes Global 2000 (2022). Their core business is to offer financial services to its clients, ranging from Investment Banking to Corporate as well as Personal Banking Services.. They are also well known for their Residential Home Loan Business.

As a Enterprise Analytics – Machine Learning Ops/AI Projects (VP1), you will be responsible for:

• Developing and maintaining automation scripts using Linux shell scripting, Python, or other relevant tools.
• Developing and maintaining the entire DevOps pipelines.
• Ensuring seamless deployment and integration between cloud/prem environments (AWS).
• Integrating AI models into production environments using containerized platforms such as OpenShift.
• Implementing and maintaining network security protocols to safeguard AI systems and data pipelines.
• Collaborating with cross-functional teams to understand AI workflows and translate them into robust engineering solutions.
• Monitoring and optimizing system performance, reliability, and scalability.
• Supporting CI/CD processes and infrastructure for AI model deployment and updates.

What you already have...

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• Bash and Unix/Linux command-line toolkit is a must-have.
• Deep technical background, with hands‑on experience in supporting CI/CD pipelines (Bitbucket, Jenkins, Artifactory, Sonar, Veracode for SAST, JIRA workflow, and Confluence).
• Hands‑on experience with OpenShift, Docker, Kubernetes.
• Knowledge of cloud platforms (e.g. AWS) is a must‑have.
• Exposure to data and network security and compliance in AI systems.
• Knowledge of API integration and microservices architecture.
• Proficiency in Python used both for automation and ML-related tasks
• Knowledge of Workflow Orchestrator, such as Ctrl‑M
• Good knowledge of Logging and Monitoring tools, such as Splunk and Geneos.
• Experience with Observability framework, such as Langfuse, Elastic Stack, Grafana, Open Telemetry.
• Understanding of Generative AI (e.g. prompt engineering, RAG pipelines) and Agentic AI concepts.