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Salary: USD 146,000 - 190,000 / annual
SpyCloud is seeking a Senior Cloud Operations Engineer to design, improve, and maintain secure, performant infrastructure powering APIs, AI operations, web applications, and data mining/ETL workflows. You will work in a fast-paced, AI-forward environment focused on disrupting cybercrime and protecting billions of accounts worldwide.
Key Responsibilities:
- Design and maintain secure, durable, and performant infrastructure to meet established SLAs, supporting APIs, AI operations, web applications, and data mining/ETL workflows
- Collaborate with developers to bring new products and services into production
- Automate testing, deployment, and monitoring across the software development lifecycle
- Continuously improve operational processes and apply best practices for scalability, security, and availability
- Proactively meet information security and compliance standards (SOC 2, ISO 27001, CMMC)
- Implement and uphold security measures across all infrastructure components
About SpyCloud:
SpyCloud transforms recaptured darknet data to disrupt cybercrime. The company provides automated identity threat protection solutions using advanced analytics and AI to accelerate investigations and protect workforce, consumer, and supplier identities. Customers include 7 of the Fortune 10, along with hundreds of global enterprises and government agencies. Headquartered in Austin, SpyCloud employs 250+ cybersecurity experts.
Requirements:
- At least 5 years of professional experience in Cloud Ops, Platform Ops, or DevOps roles maintaining production infrastructure, preferably in highly available SaaS or cloud service provider environments
- Strong working knowledge of AWS services: EC2, ECS/EKS, Lambda, API Gateway, RDS, DynamoDB, CloudWatch, S3, Code/Build/Pipeline/Deploy, VPC Lattice
- Strong working knowledge of Terraform or similar infrastructure-as-code tools, Ansible, AWS CLI/SDK, Boto
- Proficiency with scripting languages (Python, Bash) and Linux environments
- Strong understanding of system and networking concepts, troubleshooting techniques for bare metal and containerized workloads
- Experience supporting AI and ML systems, agent orchestration frameworks (e.g., AgentCore), and integrating LLMs into production systems
- Experience with release automation, system administration, configuration, and system debugging
Nice to Have:
- Databricks or Snowflake infrastructure experience
- Cost optimization for AI and LLM workloads
- Internal developer platform experience
