Responsibilities
Design, develop, test, deploy, maintain, and improve our cloud-based infrastructure, focusing on high availability, low latency, and cost-effectiveness.
Collaborate closely with engineering and research teams to integrate infrastructure components with product features, ensuring optimal system performance and user experience.
Be the subject matter expert in infrastructure when designing new products and introducing new technology to our existing product line.
Develop automation scripts, tools, and frameworks to streamline deployment, monitoring, and maintenance processes.
Implement robust security measures, adhering to industry standards and best practices, to safeguard sensitive data and prevent potential vulnerabilities.
Analyze performance metrics, identifying areas for optimization and proposing data-driven improvements.
Participate in code reviews, contribute to open-source projects, and mentor junior engineers.
Stay up-to-date with emerging trends, technologies, and methodologies, applying this knowledge to enhance our infrastructure capabilities.
Required Qualifications
Professional experience: 7+ years of design, implementation, or consulting in applications and infrastructures experience.
Education: BSc degree in Computer Science, Engineering, or a related field.
Preferred Qualifications
Technology stack
Cloud Platforms: AWS, Azure, GCP
Infrastructure as Code (IaC): Terraform, CloudFormation, Ansile, etc.
Configuration Management: Ansible, Puppet, Chef
Container Orchestration: Kubernetes, Docker Swarm
Monitoring and Logging: Prometheus, Grafana, ELK Stack (Elasticsearch, Logstash, Kibana).
Programming/ Development: Python, Node.js, Bash, Go, Ruby, CI/CD pipelines, and version control.
Education: Master’s or PhD in Computer science or related technical fields.
Professional Attributes (Code42)
Practice Humility: You ask questions even when you think you know the answer. You seek feedback early, learn from anyone regardless of title, and treat every experiment — especially the failures — as data.
Bias for Outcomes: You measure your work by what changed, not what you tried. You ship results, not slide decks. When a deadline is real, you find a way.
Care Deeply: You treat every problem as yours to solve. You review your own work with the rigor you’d want from a reviewer. You help teammates without being asked.
Dare to Do the Impossible & Embrace Scarcity: You set goals that make you uncomfortable. When told something can’t be done, you find a way or a better question. Constraints sharpen your thinking, not slow it down.
Build a Better World: You believe AI should make things meaningfully better for real people. You hold yourself accountable not just for whether your model works, but for what it does in the world.
