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
