Senior Network & Security Engineer

The Senior Network & Security Engineer role requires a minimum of five years of professional experience in enterprise networking, cybersecurity, and infrastructure security. The successful candidate will be responsible for designing, implementing, and securing network and infrastructure environments that support enterprise applications, AI/ML workloads, Kubernetes, on-premises infrastructure, and cloud platforms. This role demands a strong focus on maintaining secure connectivity across diverse environments while ensuring robust protection of data and services.

Key Responsibilities

Design, implement, and maintain secure enterprise network architectures. Configure and manage firewalls, VPNs, routers, switches, load balancers, and other network security controls. Establish secure connectivity between on-premises data centers, cloud environments, and Kubernetes clusters. Support the secure deployment of AI/ML platforms and applications across both on-premises and cloud infrastructures. 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. Ensure secure communication between frontend, backend, APIs, databases, AI/ML services, and external systems. Manage TLS/SSL certificates, encryption, secrets, and secure communication protocols. Monitor network traffic, security events, and infrastructure health, and investigate and troubleshoot network and security incidents.

Conduct security assessments to identify vulnerabilities and configuration weaknesses. Support vulnerability management, remediation, and security hardening activities. Implement Identity and Access Management (IAM) and Role-Based Access Control (RBAC). Collaborate 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 by implementing RBAC, network policies, secrets management, and workload isolation. Ensure secure communication between Kubernetes services and external enterprise systems. Support secure deployment of ML models, inference services, large language models (LLMs), retrieval-augmented generation (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 related to AI/ML workloads, including data exposure, unauthorized access, insecure APIs, and secrets leakage. Work closely with MLOps teams to establish secure model deployment and serving environments.

Cloud & Hybrid Security

Experience securing at least one major cloud platform such as AWS, Microsoft Azure, or Google Cloud Platform (GCP) is essential. Responsibilities include designing secure connectivity between cloud and on-premises environments, configuring VPC/VNet, subnets, routing, security groups, firewalls, and private endpoints. Implement cloud IAM with least-privilege access and secure cloud Kubernetes environments such as AKS, EKS, or GKE.

Support hybrid and multi-environment architectures, and implement cloud security monitoring and logging.

Required Qualifications

- Minimum of 5 years of professional experience in Network and Security Engineering.
- Strong expertise in enterprise network architecture and security.
- Deep 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.
- Proficiency in network segmentation, VLANs, routing, and access control.
- Experience with IAM, RBAC, authentication, authorization, and privileged access management.
- Solid grasp of cybersecurity principles and security best practices.
- Experience securing Linux and Windows environments.
- Familiarity with Kubernetes security is highly desirable.
- Experience with cloud networking and security.
- Knowledge of security monitoring, logging, and incident response.
- Experience with Git and infrastructure/configuration management practices.
- Strong troubleshooting and analytical skills.

Preferred Qualifications

Experience with Kubernetes and Docker is preferred, enhancing the ability to manage containerized workloads securely.

This role offers the opportunity to work at the intersection of advanced networking, cybersecurity, and emerging AI/ML technologies within complex enterprise and cloud environments.