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Senior DevSecOps

3 weeks ago

Noida, Uttar Pradesh, India CG-VAK Software & Exports Ltd. Full time

We are hiring a Senior DevSecOps / Security Engineer with 8+ years of experience securing AWS cloud, on-prem infrastructure, DevOps platforms, MLOps environments, CI/CD pipelines, container orchestration, and data/ML platforms. This role is responsible for creating and maintaining a unified security posture across all systems used by DevOps and MLOps teams — including AWS, Kubernetes, EMR, MWAA, Spark, Docker, GitOps, observability tools, and network infrastructure.

Key Responsibilities

  • Cloud Security (AWS)-
  • Secure all AWS resources consumed by DevOps/MLOps/Data Science: EC2, EKS, ECS, EMR, MWAA, S3, RDS, Redshift, Lambda, CloudFront, Glue, Athena, Kinesis, Transit Gateway, VPC Peering.
  • Implement IAM least privilege, SCPs, KMS, Secrets Manager, SSO & identity governance.
  • Configure AWS-native security: WAF, Shield, GuardDuty, Inspector, Macie, CloudTrail, Config, Security Hub.
  • Harden VPC architecture, subnets, routing, SG/NACLs, multi-account environments.
  • Ensure encryption of data at rest/in transit across all cloud services.
  • DevOps Security (IaC, CI/CD, Kubernetes, Linux)-

Infrastructure As Code & Automation Security

  • Secure Terraform, CloudFormation, Ansible with policy-as-code (OPA, Checkov, tfsec).
  • Enforce misconfiguration scanning and automated remediation.

CI/CD Security

  • Secure Jenkins, GitHub, GitLab pipelines with SAST, DAST, SCA, secrets scanning, image scanning.
  • Implement secure build, artifact signing, and deployment workflows.

Containers & Kubernetes

  • Harden Docker images, private registries, runtime policies.
  • Enforce EKS security: RBAC, IRSA, PSP/PSS, network policies, runtime monitoring.
  • Apply CIS Benchmarks for Kubernetes and Linux.

Monitoring & Reliability

  • Secure observability stack: Grafana, CloudWatch, logging, alerting, anomaly detection.
  • Ensure audit logging across cloud/platform layers.
  • MLOps Security (Airflow, EMR, Spark, Data Platforms, ML Pipelines)-

Pipeline & Workflow Security

  • Secure Airflow/MWAA connections, secrets, DAGs, execution environments.
  • Harden EMR, Spark jobs, Glue jobs, IAM roles, S3 buckets, encryption, and access policies.

ML Platform Security

  • Secure Jupyter/JupyterHub environments, containerized ML workspaces, and experiment tracking systems.
  • Control model access, artifact protection, model registry security, and ML metadata integrity.

Data Security

  • Secure ETL/ML data flows across S3, Redshift, RDS, Glue, Kinesis.
  • Enforce data versioning security, lineage tracking, PII protection, and access governance.

ML Observability

  • Implement drift detection (data drift/model drift), feature monitoring, audit logging.
  • Integrate ML monitoring with Grafana/Prometheus/CloudWatch.
  • Network & Endpoint Security-
  • Manage firewall policies, VPN, IDS/IPS, endpoint protection, secure LAN/WAN, Zero Trust principles.
  • Conduct vulnerability assessments, penetration test coordination, and network segmentation.
  • Secure remote workforce connectivity and internal office networks.
  • Threat Detection, Incident Response & Compliance-
  • Centralize log management (CloudWatch, OpenSearch/ELK, SIEM).
  • Build security alerts, automated threat detection, and incident workflows.
  • Lead incident containment, forensics, RCA, and remediation.
  • Ensure compliance with ISO 27001, SOC 2, GDPR, HIPAA (as applicable).
  • Maintain security policies, procedures, RRPs (Runbooks), and audits.

Ideal Candidate

  • 8+ years in DevSecOps, Cloud Security, Platform Security, or equivalent.
  • Proven ability securing AWS cloud ecosystems (IAM, EKS, EMR, MWAA, VPC, WAF, GuardDuty, KMS, Inspector, Macie).
  • Strong hands-on experience with Docker, Kubernetes (EKS), CI/CD tools, and Infrastructure-as-Code.
  • Experience securing ML platforms, data pipelines, and MLOps systems (Airflow/MWAA, Spark/EMR).
  • Strong Linux security (CIS hardening, auditing, intrusion detection).
  • Proficiency in Python, Bash, and automation/scripting.
  • Excellent knowledge of SIEM, observability, threat detection, monitoring systems.
  • Understanding of microservices, API security, serverless security.
  • Strong understanding of vulnerability management, penetration testing practices, and remediation plans.

Education-

  • Master's degree in Cybersecurity, Computer Science, Information Technology, or related field.
  • Relevant certifications (AWS Security Specialty, CISSP, CEH, CKA/CKS) are a plus.

Perks, Benefits and Work Culture

  • Competitive Salary Package
  • Generous Leave Policy
  • Flexible Working Hours
  • Performance-Based Bonuses
  • Health Care Benefits

Skills: devsecops,ml,data,apache spark,ci,cd,aws,airflow,devops,kubernetes,security,cloud,infrastructure