Engineering Division Global Cyber Defense & Intel Associate Bengaluru

Job Responsibilities:

• Contribute to multi-cloud platform architecture design and implementation (AWS primary Azure/GCP secondary).

• Implement network topologies IAM roles/policies and account boundaries.

• Provision and manage cloud resources using Infrastructure as Code (e.g. Terraform Ansible) and Git-based workflows.

• Participate in architecture design and change request reviews.

• Deploy configure and operate Kubernetes clusters.

• Configure and maintain core Kubernetes platform services (ingress load balancing storage autoscaling).

• Implement and maintain Kubernetes RBAC namespace structures and basic network policies.

• Troubleshoot Kubernetes workloads and cluster-level issues.

• Build and maintain container images following established standards.

• Manage and operate container registries and image promotion workflows within CI/CD pipelines.

• Integrate and operate CNCF ecosystem tools for observability (Prometheus Grafana Loki FluentBit OpenTelemetry) and deployment/configuration (Helm GitOps tools).

• Contribute to the adoption of GitOps workflows for application deployments and platform configuration management.

• Support deployment and operation of data and streaming platforms on Kubernetes (e.g. Apache Spark Flink Kafka).

• Implement storage and configuration for stateful workloads (persistence backup basic performance tuning).

• Collaborate with data engineering teams to configure resources optimize job execution and improve reliability.

• Operate and troubleshoot Linux-based systems and Kubernetes worker nodes.

• Implement hardening baselines and security configurations on Linux hosts.

• Automate OS-level configuration patching and maintenance (e.g. Bash Python Packer Ansible).

• Integrate security checks into CI/CD pipelines (container image dependency configuration/policy scanning).

• Apply policy-as-code tools (e.g. OPA Kyverno) to enforce platform guardrails.

• Implement least-privilege IAM roles encryption standards and secure secrets management.

• Participate in incident response and post-incident reviews for platform-related security/reliability events.

• Implement and manage observability tooling for metrics logs and traces across cloud and Kubernetes.

• Build and maintain dashboards alerts and runbooks for common scenarios.

• Contribute to defining and monitoring Service Level Indicators (SLIs) and SLOs.

• Assist in capacity planning performance testing and cost optimization initiatives.

• Develop and maintain reusable automation (modules pipelines scripts) for infrastructure provisioning and application deployment.

• Implement CI/CD pipelines (e.g. GitLab CI Harness) for automated build test security scanning and deployment.

• Help build self-service capabilities for development and data teams (templates APIs).

• Identify manual operational tasks and reduce toil through scripting and automation.

• Familiarity with AIOps concepts including ML-based anomaly detection for infrastructure metrics logs and security events

• Experience with predictive analytics for capacity planning resource utilization and failure prediction

• Understanding of automated root cause analysis using AI-driven correlation tools

• Familiarity with provisioning and managing GPU-enabled workloads for ML training/inference

• Understanding of ML feature pipelines using Spark Kafka and BigQuery

• Experience with AI-assisted automation for infrastructure provisioning and self-healing systems

• Familiarity with AI-powered CI/CD optimization intelligent test selection and deployment risk assessment

• Understanding of ML-driven auto-scaling and self-healing mechanisms in Kubernetes environments

• Collaborate with engineering data SRE and security teams to translate requirements into solutions.

• Document designs runbooks and standards; contribute to internal knowledge bases.

• Participate in internal training demos and brown-bag sessions to promote best practices.

• Provide guidance and informal mentoring to junior engineers.

Required Qualifications

• Bachelors degree in Computer Science Engineering or related technical field or equivalent practical experience.

• 4 years of experience in infrastructure platform or cloud engineering roles with hands-on experience in production environments.

• Strong practical experience with AWS services such as:

• VPC networking security groups and routing.

• IAM (roles policies federation).

• EC2 EKS RDS S3 SQS SNS CloudWatch and related services.

• Solid experience running workloads on Kubernetes in production including:

• Deploying and managing workloads (Deployments StatefulSets DaemonSets Jobs).

• Configuring services ingress ConfigMaps and Secrets.

• Understanding of cluster networking storage concepts and basic security controls (RBAC NetworkPolicies).

• Strong hands-on experience with containerization:

• Building secure and efficient container images.

• Working with container registries and image promotion/tagging strategies.

• Strong Linux systems skills:

• System administration networking basics shell scripting and troubleshooting.

• Automation using Bash and at least one higher-level language (e.g. Python or Go).

• Practical experience with DevSecOps practices:

• Implementing CI/CD pipelines (e.g. GitLab CI Harness Pipelines or similar).

• Integrating security and quality checks into build and deployment pipelines.

• Infrastructure as code using tools such as Terraform Ansible or CloudFormation.

• Hands-on experience with observability tooling:

• Metrics logging and tracing for distributed applications and Kubernetes (e.g. Prometheus Grafana Loki FluentBit OpenTelemetry).

• Creation of dashboards alerts and basic runbooks.

• Strong problem-solving and troubleshooting skills in distributed cloud-native environments.

• Effective communication and collaboration skills with the ability to work cross-functionally with engineering data and security teams.