Senior Network & Security Engineer

Senior Network & Security Engineer with a minimum of 5 years of professional experience in enterprise networking, cybersecurity, and infrastructure security. Will be responsible for designing, implementing, and securing network and infrastructure environments supporting enterprise applications, AI/ML workloads, Kubernetes, on-premises infrastructure, and cloud platforms.

• Design, implement, and maintain secure enterprise network architectures.
  

• Configure and manage firewalls, VPNs, routers, switches, load balancers, and network security controls.
  

• Design secure connectivity between on-premises data centers, cloud environments, and Kubernetes clusters.
  

• Support secure deployment of AI/ML platforms and applications across on-premises and cloud environments.
  

• Define network segmentation and security zones for applications, databases, AI/ML workloads, and management infrastructure.
  

• Implement and manage network access controls, firewall policies, VPNs, and secure remote access.
  

• Secure communication between frontend, backend, APIs, databases, AI/ML services, and external systems.
  

• Implement and manage TLS/SSL certificates, encryption, secrets, and secure communication protocols.
  

• Monitor network traffic, securityevents, and infrastructure health.
  

• Investigate and troubleshoot network and security incidents.
  

• Perform security assessments and identify vulnerabilities and configuration weaknesses.
  

• Support vulnerability management, remediation, and security hardening activities.
  

• Implement appropriate Identity and Access Management (IAM) and Role-Based Access Control (RBAC).
  

• Work with DevOps and MLOps teams to integrate security into CI/CD and deployment pipelines.
  

• Review infrastructure and application architectures from a security and network perspective.
  

• Establish security controls for Kubernetes clusters and containerized workloads.
  

• Support security requirements for AI/ML models, APIs, data pipelines, and AI services.
  

• Maintain network and security documentation, diagrams, configurations, and operational procedures.
  

• Participate in incident response, root-cause analysis, and security remediation activities.
  

• Secure on-premises and cloud Kubernetes environments.
  

• Implement Kubernetes RBAC, Network Policies, secrets management, and workload isolation.
  

• Secure communication between Kubernetes services and external enterprise systems.
  

• Support secure deployment of ML models, inference services, LLMs, RAG applications, and AI agents.
  

• Secure AI/ML APIs and external model-provider integrations.
  

• Implement appropriate access controls for model endpoints, data sources, vector databases, and AI services.
  

• Assess security risks associated with AI/ML workloads, including data exposure, unauthorized access, insecure APIs, and secrets leakage.
  

• Work with MLOps teams to establish secure model deployment and serving environments.
  

Experience securing at least one major cloud platform:

• AWS
  

• Microsoft Azure
  

• Google Cloud Platform (GCP)
  

Responsibilities include:

• Design secure connectivity between cloud and on-premises environments.
  

• Configure VPC/VNet, subnets, routing, security groups, firewalls, and private endpoints.
  

• Implement cloud IAM and least-privilege access.
  

• Secure cloud Kubernetes environments such as AKS, EKS, or GKE.
  

• Support hybrid and multi-environment architectures.
  

• Implement cloud security monitoring and logging.
  

• 5+ years of professional Network and Security Engineering experience.
  

• Strong experience with enterprise network architecture and security.
  

• Strong understanding of TCP/IP, DNS, DHCP, HTTP/HTTPS, TLS, VPN, routing, switching, and load balancing.
  

• Hands-on experience with enterprise firewalls and network security appliances.
  

• Experience with network segmentation, VLANs, routing, and access control.
  

• Experience with IAM, RBAC, authentication, authorization, and privileged access.
  

• Strong understanding of cybersecurity principles and security best practices.
  

• Experience securing Linux and Windows environments.
  

• Experience with Kubernetes security is highly desirable.
  

• Experience with cloud networking and security.
  

• Experience with security monitoring, logging, and incident response.
  

• Experience with Git and infrastructure/configuration management practices.
  

• Strong troubleshooting and analytical skills.