Senior Network & Security Engineer

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.

Key Responsibilities

• 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.

Kubernetes & AI/ML Security

• 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.

Cloud & Hybrid Security

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.

Required Skills & Experience

• 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.

Preferred Technologies

Experience with some of the following is preferred:

• Kubernetes

• Docker