This role is only open for candidates that are legally allowed to work within the Philippines

As a pivotal member of the engineering team, you will design, build, and maintain scalable, secure, and highly automated AWS cloud infrastructure that supports our AI-powered content management and life sciences documentation platform. Your team will lead the development and optimization of CI/CD pipelines, implement Infrastructure as Code (IaC) practices, and collaborate closely with data scientists and software engineers to operationalize machine learning models and AI workloads. Your work will directly enable rapid, reliable software and AI model deployments, ensuring high availability, security, and compliance in a regulated environment. You will drive automation and infrastructure scalability to support company’s evolving AI and MLOps capabilities.

Responsibilities

AWS Cloud Infrastructure: Architect, deploy, and manage secure, scalable cloud infrastructure using AWS services such as EC2, Lambda, S3, DynamoDB, CloudFormation, CDK, EKS, and ECS.
Infrastructure as Code: Develop and maintain IaC templates and scripts using AWS CloudFormation, AWS CDK, Terraform, or similar tools to automate provisioning and configuration, ensuring reproducibility and consistency across environments.
CI/CD Pipeline Development: Design, implement, and optimize automated CI/CD pipelines using GitLab CI/CD to enable continuous integration, testing, and deployment of both software and AI/ML models.
AI Platforms and MLOps: Collaborate with data scientists and ML engineers to deploy, monitor, and maintain machine learning models in production. Build and automate end-to-end ML pipelines, including model training, evaluation, versioning, and deployment using tools such as AWS SageMaker.
Monitoring and Observability: Implement comprehensive monitoring, logging, and alerting solutions using AWS CloudWatch and New Relic to ensure system health, performance, and security. Proactively detect and resolve issues impacting AI workloads and infrastructure.
Security and Compliance: Integrate security best practices into all stages of the infrastructure and deployment lifecycle. Manage secrets, enforce access controls, and embed compliance checks into CI/CD pipelines to meet regulatory requirements in the life sciences domain.
Automation and Optimization: Continuously identify manual processes and bottlenecks to automate using scripting languages (Python, Bash, PowerShell) and AI-driven automation tools, improving efficiency, reliability, and scalability.
Collaboration: Work cross-functionality with software engineers, data scientists, and product teams to align infrastructure and deployment strategies with business goals and AI innovation.

Requirements & Qualifications:

Strong expertise in AWS cloud services: EC2, Lambda, S3, DynamoDB, EKS, ECS, CloudFormation, CDK, IAM, CloudWatch.
Proficiency in Infrastructure as Code tools such as AWS CloudFormation, AWS CDK, Terraform.
Experience building and maintaining CI/CD pipelines with, GitLab CI/CD, AWS CodePipeline, or GitHub Actions.
Hands-on experience with AI/ML deployment and MLOps tools like MLflow, Kubeflow, AWS SageMaker.
Strong scripting skills in Python, Bash, PowerShell, or similar languages for automation.
Knowledge of monitoring and observability tools such as New Relic or AWS CloudWatch.
Solid understanding of networking, security best practices, and compliance requirements in cloud environments.
Excellent communication skills to collaborate effectively across technical and non-technical teams.
Strong problem-solving mindset with a passion for automation and continuous improvement.
Adaptability to fast-paced, evolving environments with a focus on innovation.
Team-oriented approach with a willingness to participate in on-call rotations for production support.

Nice To Have Certifications:

AWS Certified DevOps Engineer – Professional
AWS Certified Solutions Architect – Associate or Professional
AWS Certified Machine Learning – Specialty
AWS Certified Security - Specialty

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