Tech S And T - Devsecops And AI Engineer - GDSN02
Ernst Young · Bengaluru · onsite · Posted 43d ago
Undisclosed4–7 yrsfulltimeSourced from
About a minute. You'll make an account on the way through.
About this role
Designation DevSecOps & AI Engineer
Responsibilities - Build and maintain secure CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, Azure DevOps, and CircleCI for application, data, and AI workloads.
- Integrate DevSecOps practices into pipelines using Snyk, SonarQube, Checkmarx, Trivy, Anchore, and OWASP tools for continuous security scanning.
- Implement shift-left security with secret scanning (GitLeaks, TruffleHog), SBOM automation (Syft, CycloneDX), and dependency management (Dependabot, Renovate).
- Work with containerization (Docker/Podman) and Kubernetes (EKS, AKS, GKE) including Helm/Kustomize for deployments and secure image pipelines.
- Develop and automate MLOps workflows using MLflow, Kubeflow, Azure ML, SageMaker, or Vertex AI for model training, packaging, and deployment.
- Build and maintain RAG/AI integration pipelines using LangChain, LlamaIndex, Semantic Kernel, and vector databases like Pinecone, Weaviate, or FAISS.
- Implement AI inference systems using Seldon Core, KServe, BentoML, Ray Serve, or Triton Inference Server for scalable model serving.
- Automate ETL/ELT and data feature pipelines using Airflow, Prefect, Dagster, dbt, or Kafka/Kinesis for AI model data feeds.
- Work with IaC tools such as Terraform, Pulumi, CloudFormation, or Azure Bicep to provision cloud and AI infrastructure.
- Implement event-driven architectures using serverless functions (AWS Lambda, Azure Functions, Cloud Functions) and messaging systems like Kafka or RabbitMQ.
- Maintain monitoring and logging using Prometheus, Grafana, ELK/Loki, OpenTelemetry, Jaeger, Datadog, or New Relic for both app and ML workloads.
- Handle model & data observability using tools like Evidently AI, Arize AI, WhyLabs, or Fiddler for drift, bias, and performance tracking.
- Secure cloud environments using IAM best practices (AWS IAM, Azure AD/Entra ID, GCP IAM), workload identities, and least-privilege controls.
- Support configuration management using Ansible, Chef, or SaltStack for environment consistency and automation.
- Develop scripts in Python, Bash, or SQL for automation, data processing, validation, and orchestration of ML workflows.
- Implement API integrations for AI systems using REST, gRPC, or GraphQL for model consumption and downstream applications.
- Use GitOps tools like Argo CD or Flux for automated, secure Kubernetes deployments and progressive delivery.
- Apply AI security practices including guardrails, prompt protection, model validation, and safe inference techniques using industry tools.
- Ensure compliance with data governance, privacy, and security standards including GDPR, CCPA, and cloud security best practices.
- Collaborate with data engineers, ML engineers, DevOps teams, and security teams, contributing to documentation, reviews, and mentoring juniors.
- Looking for a DevSecOps & AI Engineer with 47 years of handson experience in cloud, DevOps, and AI/ML workflows.
- Strong skills in Terraform, Kubernetes, Helm, Docker, and CI/CD (GitHub Actions, GitLab CI, Jenkins, Azure DevOps).
- Proficient in Python and scripting (Bash/PowerShell) with good automation mindset.
- Experience implementing DevSecOps practicesSAST/DAST, container scanning, secrets scanning, SBOM, and policy-as-code.
- Exposure to MLOps/AI integration using MLflow, Kubeflow, SageMaker, Azure ML, KServe, or Seldon.
- Familiar with cloud (AWS/Azure/GCP), configuration management (Ansible/Puppet), and GitOps tools (Argo CD/Flux).
- Strong communication, troubleshooting, and collaboration skills with ability to work crossfunctionally.
4 to 7 years
Education B.Tech. / BS in Computer Science
Technical Skills & Certifications - Terraform, Pulumi, and Infrastructure as Code (IaC)
- Kubernetes (EKS/AKS/GKE), Docker/Podman, Helm, Kustomize
- CI/CD tools: GitHub Actions, GitLab CI, Jenkins, Azure DevOps
- Cloud platforms: AWS, Azure, GCP
- Python, Bash, PowerShell scripting
- DevSecOps tools: Snyk, SonarQube, Trivy, Checkmarx, GitLeaks, TruffleHog
- Policy-as-code (OPA/Gatekeeper, Kyverno) and SBOM tools (Syft, CycloneDX)
- MLOps tools: MLflow, Kubeflow, SageMaker, Azure ML, Vertex AI
- Model serving frameworks: KServe, Seldon Core, BentoML, Ray Serve
- Vector DBs & RAG stack: Pinecone, Weaviate, FAISS, Chroma, LangChain, LlamaIndex
- Monitoring & observability: Prometheus, Grafana, ELK/Loki, OpenTelemetry, Jaeger
- Configuration management: Ansible, Puppet
- GitOps: Argo CD, Flux
- Serverless: AWS Lambda, Azure Functions, Google Cloud Functions
Sourced from naukri
Skills
Aws LambdaAutomationBashAzure DevopsAI infrastructureai integrationaws iamai modelamazon web servicesAksCcpabsapache airflowcd toolsai engineerazure mlAzure ADai securityCapital MarketsMicrosoft AzureAnsibleAzure FunctionsbicepArtificial Intelligence
About Ernst & Young
Ernst Young
Management Consulting
44k+
employees
2002
24 years old
Gurgaon / Gurugram, Haryana
India
₹15.3L PA avg
Avg at Ernst & Young
About
At EY, our purpose is Building a better working world. The insights and quality services we provide help build trust and confidence in the capital markets and in economies the world over.
Industries
Management Consulting
Employee ratings
10 reviews
3.4/ 5
Culture
1.9
Career growth
2.3
Work-life
2.5
Employees rate it well for
Job Security36Skill Development35
Find them on