NTT DATA
Website:
nttdata.com
Job details:
As a Senior Cloud DevSecOps Engineer, you will design, implement, and operate secure, scalable cloud infrastructure and DevSecOps pipelines for AI-powered applications deployed on AWS within highly regulated banking environments. You will ensure infrastructure reliability, security, compliance, and operational excellence across AI/ML workloads, cloud-native systems, and financial services platforms.
You will lead the implementation of secure CI/CD pipelines, container orchestration, and automated security controls for AI systems and data pipelines. You will embed security and compliance practices across the software development lifecycle (SDLC), ensuring adherence to banking regulatory standards and EU AI compliance requirements.
This is a hands-on engineering role where you will collaborate with AI engineers, security teams, cloud architects, risk/compliance teams, and banking stakeholders to deliver production-grade, compliant, and resilient AI/cloud platforms.
You will continuously monitor cloud environments, manage vulnerabilities, implement security controls, and ensure governance frameworks align with EU AI regulations, financial regulatory requirements, and internal risk management policies.
What You’ll Bring
- 8+ years of hands-on experience in Cloud Engineering, DevOps, or DevSecOps roles.
- Strong experience designing and managing AWS-based cloud infrastructure in production environments.
- Proven experience implementing DevSecOps practices in regulated industries (banking/financial services preferred).
- Experience supporting AI/ML or data-driven workloads in cloud environments.
- Strong understanding of cloud security, governance, and compliance frameworks.
- Knowledge of EU AI regulatory requirements and responsible AI governance practices.
- Experience working in highly regulated banking or financial institutions.
- Ability to independently architect, secure, and operate cloud-native systems.
- Degree in Computer Science, Engineering, Cybersecurity, or related field — or equivalent practical experience.
Skill Requirements
- Strong hands-on experience with AWS services (EC2, S3, IAM, RDS, Lambda, ECS/EKS, API Gateway, CloudWatch, VPC, KMS, etc.)
- Experience implementing Infrastructure as Code using Terraform, CloudFormation, or similar tools
- Strong experience building secure CI/CD pipelines using Jenkins, GitHub Actions, GitLab CI, or AWS CodePipeline
- Experience integrating automated security testing (SAST, DAST, SCA, container scanning, IaC scanning) into pipelines
- Hands-on experience with containerization and orchestration (Docker, Kubernetes, EKS preferred)
- Experience implementing zero-trust architecture, IAM policies, encryption (at rest/in transit), and secrets management
- Knowledge of AWS security best practices, Well-Architected Framework, and cloud governance models
- Experience securing AI/ML workloads, model endpoints, data pipelines, and vector databases
- Understanding of EU AI compliance principles (risk classification, transparency, model governance, documentation, auditability)
- Familiarity with GDPR, data residency requirements, and financial regulatory controls
- Experience implementing logging, monitoring, and incident response using CloudWatch, ELK, Prometheus, or similar tools
- Strong understanding of DevSecOps principles, threat modeling, and secure SDLC practices
- Experience with vulnerability management, penetration testing coordination, and remediation tracking
- Strong scripting skills (Python, Bash, or similar)
- Experience with Git workflows and branch protection strategies
- Knowledge of disaster recovery (DR), high availability (HA), and business continuity planning in banking systems
Typical Senior Cloud DevSecOps Engineer Roles And Responsibilities
- Design secure, scalable AWS infrastructure for AI and banking applications.
- Implement Infrastructure as Code (IaC) to standardize cloud deployments.
- Build and maintain secure CI/CD pipelines with embedded security controls.
- Implement automated security testing across application, container, and infrastructure layers.
- Ensure AI systems meet EU AI regulatory requirements and internal compliance standards.
- Collaborate with risk and compliance teams to document AI system governance and audit trails.
- Implement encryption, identity management, network segmentation, and secure access controls.
- Secure AI/ML model endpoints, training environments, and data pipelines.
- Monitor cloud environments for vulnerabilities, misconfigurations, and threats.
- Conduct cloud security assessments and support regulatory audits.
- Implement logging, monitoring, and alerting frameworks for production AI workloads.
- Ensure data privacy, residency, and governance standards are met in banking environments.
- Support disaster recovery planning and high-availability system architecture.
Troubleshoot infrastructure, deployment, and security-related pro
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