Senior DevSecOps Engineer

Job Title: DevSecOps Senior Engineer

Interview Mode: Face-to-FaceKey Requirement: Candidates must be authorized to work in the U.S. for any employer on a W-2 basis without requiring current or future visa sponsorship. Qualified candidates who meet these requirements are encouraged to apply. WHAT’S NEEDEDMinimum Educational Qualifications - BS/MS degree 5-10 years of experience in DevOps, DevSecOps, Platform Engineering, Cloud Engineering, or related disciplines supporting enterprise-scale applications and distributed systems.3+ years of experience in a senior technical role such as DevSecOps Lead, Platform Engineer, Senior DevOps Engineer, or Site Reliability Engineer (SRE).Strong hands-on experience with AWS cloud services including EKS/ECS, Lambda, IAM, VPC, CloudWatch, S3, RDS, Kinesis, MQ, RedShift, Secrets Manager, SNS, SQS, EventBridge, ElastiCache etc. Design, build, and maintain CI/CD pipelines using Jenkins, GitLab CI/CD, GitHub Actions, AWS Code Pipeline, ArgoCD, or similar technologies. Implement Infrastructure as Code (IaC) using Terraform, Cloud Formation, Helm, and related automation frameworks. Strong experience with Docker, Kubernetes, Amazon EKS, and container platform operations. Implement DevSecOps practices including vulnerability management, secrets management, policy enforcement, compliance validation, and software supply chain security. Strong knowledge of cloud security including IAM, RBAC, encryption, OAuth2/OIDC, JWT, network security, and Zero Trust principles. Build and manage observability, monitoring, logging, and alerting solutions using CloudWatch, Prometheus, Grafana, ELK/OpenSearch, Datadog, Splunk, or similar tools. Programming experience in Python, Bash, Go, or similar scripting languages. Drive platform reliability, resiliency, operational excellence, disaster recovery, and production readiness. Experience leveraging AI-assisted engineering tools such as GitHub Copilot, Amazon Q, OpenAI, Claude, Cursor, or similar technologies to improve developer productivity, automation, troubleshooting, and operational efficiency. Familiarity with enterprise AI/LLM concepts including Prompt Engineering, RAG, Vector Databases, AI Agents, LLMOps, AI Security Guardrails, and Responsible AI practices. Collaborate with development, architecture, security, and infrastructure teams to improve platform scalability, security posture, developer experience, and engineering productivity. Lead cloud modernization, automation, platform engineering, and DevSecOps initiatives while mentoring engineering teams on best practices.