About the Role
We are looking for a highly skilled and dedicated DevOps Engineer to join our growing engineering team in a remote capacity. This pivotal role is exclusively open to candidates legally authorized to work within the Philippines and offers a unique opportunity to design, build, and maintain a highly automated AWS cloud infrastructure. You will be responsible for supporting a sophisticated AI-powered content management platform specifically designed for life sciences documentation. By bridging the gap between software engineering and data science, you will ensure our systems remain scalable, secure, and compliant within a strictly regulated environment, directly impacting the speed and reliability of our AI model deployments.
Key ResponsibilitiesAs a core member of our infrastructure team, your primary focus will be the architecture and management of secure AWS cloud services, including EC2, Lambda, S3, DynamoDB, EKS, and ECS. You will champion Infrastructure as Code (IaC) by developing and maintaining robust templates and scripts using AWS CDK, CloudFormation, or Terraform, ensuring that our environments are consistent, reproducible, and easily scalable. A significant portion of your role involves designing and optimizing automated CI/CD pipelines through GitLab to facilitate the continuous integration and deployment of both traditional software components and complex AI/ML models.
Collaboration is central to this role; you will work hand-in-hand with data scientists and ML engineers to operationalize machine learning models using tools like AWS SageMaker. This includes building end-to-end ML pipelines that handle everything from training and evaluation to versioning and production deployment. You will also be responsible for maintaining system health through proactive monitoring and observability, utilizing AWS CloudWatch and New Relic to detect and resolve performance bottlenecks before they impact our AI workloads. Furthermore, you will embed security best practices and compliance checks throughout the deployment lifecycle to protect sensitive life sciences data and meet stringent regulatory standards.
QualificationsThe ideal candidate possesses deep technical expertise in the AWS ecosystem and a passion for automation. You must demonstrate proficiency in Infrastructure as Code tools and have a proven track record of building and maintaining complex CI/CD pipelines using GitLab or similar platforms. We require hands-on experience with MLOps tools such as MLflow or AWS SageMaker, as your work will directly support machine learning workflows. Strong scripting abilities in Python, Bash, or PowerShell are essential for driving efficiency and eliminating manual bottlenecks across our cloud environments.
- Extensive experience with core AWS services including Lambda, DynamoDB, EKS, and IAM.
- Solid understanding of networking, cloud security best practices, and regulatory compliance.
- Exceptional problem-solving skills and a proactive mindset toward system optimization.
- Clear communication skills to effectively collaborate with cross-functional technical teams.
- A team-oriented approach with the flexibility to participate in on-call rotations for production support.
- Professional certifications such as AWS Certified DevOps Engineer or Solutions Architect are highly preferred.
Joining our team means working at the intersection of artificial intelligence and life sciences innovation. We offer a fully remote work environment that provides the flexibility to maintain a healthy work-life balance while contributing to high-impact projects. You will have the chance to work with a modern tech stack and advance your career in the rapidly evolving field of MLOps. We provide a collaborative atmosphere where continuous learning is encouraged, and your contributions to automation and infrastructure scalability will be recognized as a key driver of our companys success.