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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and maintaining secure CI/CD pipelines, integrating DevSecOps practices, and automating MLOps workflows. Proficient in cloud infrastructure provisioning and implementing scalable AI systems while ensuring compliance with data governance and security standards.
Highest-signal resume keywords
CI/CD Pipeline DevelopmentDevSecOps ImplementationMLOps Workflow AutomationKubernetes ManagementCloud Infrastructure Provisioning
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Build and maintain secure CI/CD pipelines for application, data, and AI workloads
- Integrate DevSecOps practices and continuous security scanning into pipelines
- Implement secret scanning, SBOM automation, and dependency management
- Deploy and manage containerized workloads on Kubernetes using Helm and Kustomize
- Develop and automate MLOps workflows for model training, packaging, and deployment
- Build RAG and AI integration pipelines using orchestration frameworks and vector databases
- Implement scalable AI inference and model-serving systems
- Automate ETL/ELT and data feature pipelines for AI model data feeds
- Provision cloud and AI infrastructure with infrastructure-as-code tools
- Implement event-driven architectures with serverless functions and messaging systems
- Maintain application and ML monitoring, logging, and observability
- Track model and data drift, bias, and performance
- Secure cloud environments using IAM, workload identities, and least-privilege controls
- Support configuration management and environment automation
- Develop Python, Bash, or SQL scripts for automation and ML workflow orchestration
- Implement REST, gRPC, and GraphQL API integrations for AI systems
- Use GitOps tools for secure Kubernetes deployments and progressive delivery
- Apply AI security practices including guardrails, prompt protection, model validation, and safe inference
- Ensure compliance with GDPR, CCPA, data governance, privacy, and cloud security standards
- Collaborate with data engineers, ML engineers, DevOps teams, and security teams; contribute to documentation, reviews, and mentoring juniors
Requirements
What you’ll need- 4–7 years of hands-on experience in cloud, DevOps, and AI/ML workflows
- Strong skills in Terraform, Kubernetes, Helm, Docker, and CI/CD tools including GitHub Actions, GitLab CI, Jenkins, and Azure DevOps
- Proficiency in Python and scripting with Bash or PowerShell
- Experience implementing DevSecOps practices including SAST/DAST, container scanning, secrets scanning, SBOM, and policy-as-code
- Exposure to MLOps/AI integration using MLflow, Kubeflow, SageMaker, Azure ML, KServe, or Seldon
- Familiarity with AWS, Azure, or GCP; Ansible or Puppet; and Argo CD or Flux
- Strong communication, troubleshooting, and collaboration skills with ability to work cross-functionally
- B.Tech. or BS in Computer Science
- Knowledge of Terraform, Pulumi, IaC, Kubernetes, Docker/Podman, Helm, Kustomize, CI/CD, AWS/Azure/GCP, Python, Bash, PowerShell, DevSecOps tools, policy-as-code, SBOM tools, MLOps tools, model-serving frameworks, vector databases, RAG tools, monitoring and observability tools, configuration management, GitOps, and serverless platforms
Benefits
Comp & perks- No specific benefits, perks, or compensation extras are stated in the posting
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PythonBashTerraformKubernetesHelmDockerCI/CD ToolsMLOps ToolsAPI IntegrationInfrastructure-as-Code
Soft Skills
Strong CommunicationTroubleshootingCollaboration
Tools & Technologies
GitHub ActionsGitLab CIJenkinsAzure DevOpsAWSAzureGCPAnsiblePuppetArgo CD
Industry Keywords
DevSecOpsGDPRCCPAData GovernanceCloud SecurityModel ServingVector DatabasesEvent-Driven ArchitectureMonitoring and ObservabilityConfiguration Management