Senior DevSecOps Engineer

Role & Responsibilities

The Senior DevSecOps Engineer will be responsible for the operationalisation, security, compliance, and production readiness of the data and ML platform.

• Operationalise and deploy ML models into production, working closely with Data Scientists during the transition from model development to deployment.
• Manage ML infrastructure and monitor model performance, reliability, and accuracy in production.
• Manage the configuration, deployment, and operational readiness of the data platform within the Government Commercial Cloud (GCC) environment.
• Own platform security and compliance, ensuring alignment with IM8, GCC security baselines, PDPA, and other applicable data compliance requirements.
• Implement infrastructure security and data privacy controls, including PII redaction, anonymisation, and blurring of sensitive information from sources such as CCTV feeds.
• Establish and maintain data quality standards covering completeness, accuracy, format and schema compliance, and latency.
• Build and validate automated data quality checks within data pipelines.
• Develop infrastructure runbooks covering deployment, configuration, monitoring, troubleshooting, and incident response.
• Work closely with internal teams to progressively transfer MLOps, security, compliance, and data quality capabilities.

Requirements

• Degree in Computer Science, Engineering, Information Security, or a related field.
• 8+ years of relevant experience in MLOps, DevSecOps, security engineering, cloud infrastructure, or compliance.
• Proven experience deploying and operationalising ML models in production, including model monitoring and performance management.
• Strong hands-on experience with AWS cloud infrastructure, including cloud security and compliance requirements.
• Experience deploying and operating data platforms such as Databricks or comparable platforms, from initial implementation through production monitoring and incident response.
• Hands-on experience with government or public-sector security and compliance frameworks, preferably within GCC environments.
• Experience implementing data privacy controls, including PII redaction and anonymisation.
• Experience securing large-scale, high-sensitivity government or public-sector platforms, preferably serving as a lead Security, DevSecOps, or MLOps Engineer for a significant portion of the project lifecycle.
• Demonstrated experience delivering comparable large-scale data platform projects internationally, at city-level or above, outside the Singapore market.
• Strong understanding of data quality dimensions, including completeness, accuracy, format compliance, schema conformance, and latency, with experience implementing automated validation within data pipelines.
• Strong communication and stakeholder management skills, with the ability to transfer technical capabilities and knowledge to internal teams.