Site Reliability Engineer

Recruiting From Scratch•San Francisco, NY

15h•$140,000 - $180,000•Onsite

About The Position

Our client is building revolutionary AI thought partners that are transforming how knowledge is created and shared in financial services. They're an unabashedly ambitious team with exceptional traction among the world's largest investment banks, hedge funds, and private equity firms. With a lean, smart, and enormously ambitious team working from their beautiful NYC office, they're on track to become the biggest Financial AI company in the world. This isn't just another tech startup - they're pushing the boundaries of published research, redefining what's possible with AI, and literally inventing the future of financial knowledge work. Their platform is crazily powerful, creating tools that make people smarter and revolutionizing how knowledge is discovered, created, and shared.

Requirements

Bachelor's degree in Computer Science, Information Technology, or related field
3-5 years of hands-on experience with AWS and/or Azure cloud platforms, including services like EC2, S3, VPC, and Lambda
2-3 years of experience managing Kubernetes clusters in production environments
2-3 years of experience with Helm for Kubernetes package management
2-3 years of experience with Datadog or similar monitoring tools
3-5 years of experience with Linux system administration and shell scripting
2-3 years of experience with Infrastructure as Code (IaC) tools like Terraform
Proficiency in scripting languages such as Bash and Python
Strong understanding of networking fundamentals, including TCP/IP, DNS, and load balancing
Experience with CI/CD pipelines and tools like Jenkins, GitLab CI, or GitHub Actions
Knowledge of cloud-native security best practices and compliance frameworks
Excellent problem-solving skills and ability to navigate complex challenges effectively
Strong communication and collaboration skills

Nice To Haves

Experience with MLOps monitoring and observability
Experience with PostgreSQL, Elasticsearch, and vector databases such as Qdrant or similar technologies
Experience with monitoring and security tools such as Datadog, AWS GuardDuty, CloudWatch, and CloudTrail
Certifications in AWS, Azure, or Kubernetes
Experience with other cloud platforms like Google Cloud Platform (GCP)
Experience with distributed tracing and observability tools

Responsibilities

Infrastructure Magic: Design, deploy, and maintain cloud infrastructure on AWS and/or Azure that powers cutting-edge AI systems, ensuring high availability and resilience
Performance Guardian: Implement and manage sophisticated monitoring solutions using Datadog to proactively identify and address system issues before they impact users
Kubernetes Commander: Manage production Kubernetes clusters and utilize Helm for package management and deployment automation
Automation Wizard: Develop and maintain Infrastructure as Code (IaC) using Terraform and create automation scripts in Bash or Python to streamline operations
Collaboration Champion: Work closely with development and operations teams to foster DevOps culture, share best practices, and ensure seamless integration and deployment processes
Problem Solver: Troubleshoot and resolve complex cross-platform issues related to OS, networking, and databases in a cloud-based environment
Knowledge Keeper: Maintain comprehensive documentation of system configurations, procedures, and troubleshooting guides