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 ProgrammingAutomation & Scripting : Python scripting for automation, Linux shell scriptingOperating Systems & Containers
System programing, performance tuning, networkingOCP, Kubernetes (K8s), Helm, Terraform, container orchestration and deploymentBig 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, MinIOData Formats : Parquet / Avro, ORC, JSON, CSVAI / ML & MTC (Model Training & Consumption) (Nice to have)
Frameworks or LLM modelingModel Ops : MLflow, Kubeflow, SageMakerData Science : Feature engineering, model deployment, inference pipelinesSecurity & 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 policiesSystem Design & Architecture (good to have, at least at conceptual level)
Design Principles : Microservices, Event-driven architecture, ServerlessScalability : Load balancing, caching (Redis, Memcached), horizontal scalingHigh Availability : Failover strategies, disaster recovery, monitoring (Prometheus, Grafana)