Platform Engineer

SEDHA CONSULTING PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

SEDHA CONSULTING PTE. LTD. seeks a Platform Engineer to manage AI infrastructure projects and support stakeholders in a fast-paced setting. You will translate requirements into scalable platform designs and collaborate across service providers to deploy secure, resilient AI systems.

Responsibilities include overseeing AI platform operations, improving runbooks, and advancing automation. Strong knowledge of AWS, Linux, Python, and IaC is preferred.

Qualifications

• Hands-on experience building and operating enterprise AI platforms on AWS or on-prem.
• Experience with DevSecOps, MLOps, or LLMOps pipelines.
• Proficient in Infrastructure-as-Code and Python.
• Knowledge of PostgreSQL, vector databases, and data processing.
• Understanding AI and infrastructure security risks and controls.
• Strong communication and ability to influence stakeholders.

Responsibilities

• Deliver projects to meet platform availability, reliability, and resilience requirements.
• Translate business requirements into platform infrastructure designs.
• Collaborate with providers to design, deploy, and configure AI infrastructure.
• Ensure compliance with Enterprise Architecture, Security Standards, and AI policies.
• Act as point-of-contact for new AI product initiatives and testing.
• Manage AI platform operations and support Data Scientists and Product Managers.
• Improve runbooks and SOPs to meet compliance mandates.
• Improve AI platform experience with new features and enhancements.
• Automate to simplify development and operations with reusable services.
• Assist in AI platform design reviews and security standards improvement.
• Onboard hosting environments by designing, configuring, and testing infrastructure.
• Manage architecture, resource planning, and hosting across servers, OS, and containers.

Skills

Communication

Stakeholder management

Problem solving

DevSecOps

MLOps

Tools

AWS

On-prem

Python

Container tech

Linux

CI/CD

Monitoring

Job description

Job Summary

As an Platform Engineer, you will manage multiple priorities in a fast-paced environment while supporting stakeholder needs and responding to change. Specifically, you are expected to:

Key Responsibilities

• Deliver projects within the assigned practice to meet platform availability, reliability and resilience requirements.


• Translate business requirements into platform infrastructure designs.


• Work with service providers to design, deploy and configure resilient, available and secure AI infrastructure.


• Ensure compliance with the Authority's Enterprise Architecture and Security Standards, as well as IM8 and AI Policies.


• Act as the point-of-contact for new AI product initiatives, supporting system design, integration, acceptance and performance testing.


• Manage AI platform operations and address queries from Data Scientists and Product Managers.


• Improve operational runbooks, SOPs and adhere to enterprise and compliance mandates.


• Continually improve AI platform experience by implementing new features and enhancements.


• Continually simplify product development and operations through automation and building reusable services.


• Assist in AI Platform design review and improvement of AI, OS, container and database security standards.


• Onboard hosting environments by designing, setting up, configuring, implementing, testing and commissioning the required infrastructure.


• Manage system architecture, resource planning, platform performance, and hosting across servers, operating systems, and containers, excluding hypervisor and storage layers.

What we are looking for

• Strong written and verbal communication skills, with the ability to pitch ideas, influence stakeholders and balance strategic perspective with business needs and challenges.


• Ability to assess project and compliance requirements and develop practical, sustainable solutions.


• Hands-on experience building, securing and operating enterprise Data Science and AI platforms on AWS or in on-premises environments.


• Hands-on experience building and operating DevSecOps, MLOps, and/or LLMOps pipelines.


• Hands-on experience with AI and container services, LLM inference and Linux preferred.


• Hands-on experience with Infrastructure-as-Code, automation and Python tech stack preferred.


• Experience working with Identity & Access Management services (e.g. Entra ID, AWS Cognito and AWS IAM), and Monitoring & Observability services (e.g. CloudWatch, Splunk and Elastic) are advantageous.


• Knowledge of PostgreSQL, vector databases, object storage, and the processing of structured and unstructured datasets is advantageous.


• Good understanding of AI, application and infrastructure security risks and controls.