Senior Platform Engineer, Taxfix

• The ideal candidate will have deep technical and programmatic expertise in cloud-native security, along with demonstrable hands-on experience securing AI/ML systems
• 5+ years of experience in information security, with at least 3 years specializing in cloud security
• 3+ years of hands-on experience securing containerized environments (Docker, Kubernetes)
• Demonstrable hands-on experience securing AI/ML or LLM-based systems
• Strong background in at least one major cloud provider (AWS, Azure, GCP)
• Expert knowledge of container security, Kubernetes security, and cloud-native security patterns
• Proficiency with Infrastructure as Code tools (Terraform, CloudFormation, etc.)
• Strong understanding of network security, identity management, and access control
• Experience with security tooling for cloud environments (Cloud Security Posture Management, CSPM)
• Working knowledge of AI/ML and LLM security, including familiarity with frameworks like TensorFlow and PyTorch and their security implications
• Proficiency in scripting and programming languages (Python, Go, Bash)
• Experience with security automation and orchestration
• Not sure if you meet all the requirements for this role? Please apply anyway. You might bring something special to the team that we hadn't considered previously

Desirable

• We are seeking an experienced Senior Platform Security Engineer to design, implement, and maintain security solutions for our cloud-native infrastructure and AI systems
• This role will be responsible for securing our platform across multiple cloud environments, ensuring container and Kubernetes security, protecting AI/ML workflows, and implementing robust security controls throughout our SDLC
• Cloud & Infrastructure Security:
• Design and implement comprehensive security architectures for cloud platforms (AWS, Azure, GCP)
• Implement security best practices for container and Kubernetes deployments
• Develop and maintain secure Infrastructure as Code (IaC) codebases
• Design and deploy zero-trust network architecture and secure service mesh solutions
• Build and maintain secure CI/CD pipelines following DevSecOps principles
• AI/ML Security:
• Secure AI-powered product features end to end, covering context assembly, tool invocation, and output handling
• Design and review security controls for RAG implementations
• Secure agentic solutions and their extension points: tool integrations (MCP clients and servers), agent skills, and autonomous action boundaries such as scoped credentials, sandboxing, and human-in-the-loop gates
• Build defenses against direct and indirect prompt injection and other adversarial inputs to LLM applications
• Establish data security controls for sensitive data flowing through inference, retrieval, and fine-tuning
• Security Operations:
• Lead incident response for cloud and AI infrastructure security incidents
• Develop and implement security monitoring and detection strategies
• Conduct threat modeling and risk assessments for cloud-native and AI systems
• Perform regular security assessments of cloud infrastructure and container deployments
• Create and maintain security documentation, including policies, procedures, and run-books
• Leadership & Collaboration:
• Collaborate with development, data science, and operations teams to integrate security
• Communicate security requirements and recommendations to technical and non-technical stakeholders
• Stay current with emerging threats and security trends in cloud-native and AI security
• Participate in technology selections for security tooling and platforms