Senior Engineer II, Cloud Native – AI Detection and Response

• Architect and build the next generation of AI Detection and Response (AIDR) cloud services
• Process millions of AI security events per second and manage petabytes of critical AI data
• Architect enterprise-grade solutions scaling from thousands to millions of requests per second
• Build reusable platform libraries for multiple engineering teams
• Drive operational excellence through rapid issue resolution, root cause analysis, and proactive system improvements
• Collaborate across engineering teams to drive testing best practices
• Design and implement scalable microservices, frameworks, and platform components
• Develop comprehensive reliability, accuracy, and performance tests
• Conduct code and design reviews focused on testability, security, and scalability
• Integrate with Crowd Strike ecosystem services and APIs
• Analyze production issues and implement preventive measures
• Mentor team members on secure coding, testing methodologies, and cloud-native development

• 10+ years of software development experience building enterprise-grade products
• 5+ years of experience developing microservices in cloud-native environments
• Strong computer science fundamentals in algorithms, data structures, and distributed systems
• Expertise in at least one cloud-native programming language:
  Go, Python, or Java
• Proven experience using AI technologies to enhance decision-making, streamline workflows and processes, improve efficiency, and drive business outcomes
• Deep understanding of cloud architectures and microservices
• Experience with REST, gRPC, Protocol Buffers, or similar API technologies
• Experience with PostgreSQL, Redis, or similar databases
• Experience with Docker, Kubernetes, or similar orchestration platforms
• Proven track record deploying services to at least one cloud environment: AWS, OCI, GCP, or Azure
• Strong debugging skills for complex distributed systems
• Experience with cloud monitoring, profiling, and optimization tools
• Bonus: cybersecurity or security-focused product experience
• Bonus: AI/ML security knowledge
• Bonus: real-time data processing systems such as Kafka, Pulsar, or Splunk
• Bonus: open-source library or framework contributions
• Bonus: GCP, OCI, Kubernetes, AWS, API Gateway, Golang, MS Copilot Ecosystem, MS Agent Studio, MLOps, ML model evaluation, MLflow, Kubeflow, Sage Maker, Vertex AI, Azure ML, CI/CD pipelines, model versioning, A/B testing, canary deployments, explainability tools, and ML observability platforms

Demonstrates expertise in architecting and building scalable AI Detection and Response cloud services, with a strong focus on microservices, cloud-native development, and operational excellence. Proven ability to mentor teams on secure coding practices and implement comprehensive testing methodologies.

• Microservices Development
• Cloud-Native Programming (Go, Python, Java)
• AI Technologies Integration
• Cloud Architecture Expertise
• Distributed Systems Debugging

• Software Development
• Microservices
• Algorithms
• Data Structures
• Distributed Systems
• REST APIs
• GRPC
• PostgreSQL
• Docker
• Kubernetes

• Mentoring
• Collaboration
• Problem Solving

• AI Detection and Response
• Cloud Services
• Operational Excellence
• Security-Focused Products
• Real-Time Data Processing

• AWS
• GCP
• Azure
• CI/CD Pipelines
• Kafka
• Pulsar
• Splunk
• MLflow
• Kubeflow
• Sage Maker