Cloud Security EngineerMotion Recruitment • Charlotte, NC, United States

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Cloud Security Engineer

Motion Recruitment • Charlotte, NC, United States

[job_card.variable_days_ago]

[job_preview.job_type]

[job_card.full_time]

[job_card.job_description]

We are looking for a Security-Focused Platform Engineer / Site Reliability Engineer to maintain secure, scalable infrastructure and services. This role is responsible for ensuring operational reliability while embedding security into all aspects of infrastructure and platform engineering.

W2 position - No C2C at this time

Key Responsibilities

Maintain secure and scalable infrastructure and services.

Manage container orchestration and cloud security.

Monitor for configuration drift and enforce infrastructure policies.

Support high availability and secure deployment and operations practices.

Implement infrastructure-as-code with security controls.

Monitor system health and enforce runtime policies.

Collaborate with stakeholders on secure service mesh, events, and API gateways.

Qualifications

Experience maintaining scalable and secure infrastructure.

Background in container orchestration and cloud security.

Ability to identify and remediate configuration drift.

Knowledge of high availability and secure deployment practices.

Hands-on experience with infrastructure-as-code and security controls.

Ability to monitor system health and enforce runtime policies.

Experience collaborating with stakeholders on secure service mesh, events, and API gateways.

Programming & Scripting Used

Languages : Python, Bash, Shell, SQL, Java (basic), Scala (for big data, good to have)

Paradigms : Object-Oriented Programming (OOP), Functional Programming

Automation & Scripting : Python scripting for automation, Linux shell scripting

Operating Systems & Containers

System programing, performance tuning, networking

OCP, Kubernetes (K8s), Helm, Terraform, container orchestration and deployment

Big Data & Data Engineering

Frameworks : Apache Spark, Hadoop, Hive, Presto (nice to have)

ETL Tools : Apache Airflow, NiFi (good to have)

Data Pipelines : Batch and streaming (Kafka, Flink)

Object Storage : S3, Azure Blob Storage, MinIO

Data Formats : Parquet / Avro, ORC, JSON, CSV

AI / ML & MTC (Model Training & Consumption) (Nice to have)

Frameworks or LLM modeling

Model Ops : MLflow, Kubeflow, SageMaker

Data Science : Feature engineering, model deployment, inference pipelines

Security & Access Control

Access Models : RBAC (Role-Based Access Control), ABAC (Attribute-Based Access Control)

Data Protection : Encryption at rest and in transit, TLS / SSL, KMS (Key Management Services)

Compliance : GDPR, HIPAA (if applicable), IAM policies

System Design & Architecture (good to have, at least at conceptual level)

Design Principles : Microservices, Event-driven architecture, Serverless

Scalability : Load balancing, caching (Redis, Memcached), horizontal scaling

High Availability : Failover strategies, disaster recovery, monitoring (Prometheus, Grafana)

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