{"id":2999535,"url":"https://alion.io/job/ey-tech-s-and-t-network-engineer-senior-gdsn02","title":"Tech S And T - Network Engineer Senior - GDSN02","company":{"id":2859,"name":"EY","domain":"ey.com","url":"https://alion.io/company/ey-com","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"Networking","role_family":"Networking","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Noida, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":16000,"max_usd":38000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":731},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon EKS","optional":false},{"name":"Amazon Kinesis","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"Ansible","optional":false},{"name":"Apache Kafka","optional":false},{"name":"ArgoCD","optional":false},{"name":"Arize Phoenix","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"Azure","optional":false},{"name":"Azure AKS","optional":false},{"name":"Azure DevOps","optional":false},{"name":"BentoML","optional":false},{"name":"Bicep","optional":false},{"name":"Checkmarx","optional":false},{"name":"Chef","optional":false},{"name":"Chroma","optional":false},{"name":"CI/CD","optional":false},{"name":"CircleCI","optional":false},{"name":"CloudFormation","optional":false},{"name":"Configuration Management","optional":false},{"name":"Dagster","optional":false},{"name":"Datadog","optional":false},{"name":"dbt","optional":false},{"name":"Dependabot","optional":false},{"name":"Docker","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Evidently AI","optional":false},{"name":"FAISS","optional":false},{"name":"GCP","optional":false},{"name":"GDPR","optional":false},{"name":"GitHub Actions","optional":false},{"name":"GitLab CI","optional":false},{"name":"Gitleaks","optional":false},{"name":"GitOps","optional":false},{"name":"Google GKE","optional":false},{"name":"Grafana","optional":false},{"name":"GraphQL","optional":false},{"name":"gRPC","optional":false},{"name":"Helm","optional":false},{"name":"IAM","optional":false},{"name":"Jaeger","optional":false},{"name":"Jenkins","optional":false},{"name":"KServe","optional":false},{"name":"Kubeflow","optional":false},{"name":"Kubernetes","optional":false},{"name":"Kustomize","optional":false},{"name":"Kyverno","optional":false},{"name":"LangChain","optional":false},{"name":"Least Privilege","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Loki","optional":false},{"name":"Microsoft Entra ID","optional":false},{"name":"MLFlow","optional":false},{"name":"New Relic","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"OWASP","optional":false},{"name":"Pinecone","optional":false},{"name":"Podman","optional":false},{"name":"PowerShell","optional":false},{"name":"Prefect","optional":false},{"name":"Progressive Delivery","optional":false},{"name":"Prometheus","optional":false},{"name":"Pulumi","optional":false},{"name":"Puppet","optional":false},{"name":"Python","optional":false},{"name":"RabbitMQ","optional":false},{"name":"RAG","optional":false},{"name":"Ray Serve","optional":false},{"name":"Renovate","optional":false},{"name":"Rest API","optional":false},{"name":"SaltStack","optional":false},{"name":"SBOM","optional":false},{"name":"Seldon Core","optional":false},{"name":"Semantic Kernel","optional":false},{"name":"Shift-Left Security","optional":false},{"name":"Snyk","optional":false},{"name":"SonarQube","optional":false},{"name":"SQL","optional":false},{"name":"Syft","optional":false},{"name":"Terraform","optional":false},{"name":"Triton Inference Server","optional":false},{"name":"Trivy","optional":false},{"name":"TruffleHog","optional":false},{"name":"Vertex AI","optional":false},{"name":"Weaviate","optional":false},{"name":"Ray","optional":true}],"status":"live","first_seen_at":"2026-10-21T11:37:23Z","employer_posted_date":"2026-10-21","last_verified_at":"2026-11-02T00:03:37Z","board_verified":true,"closed_at":null,"days_open":11,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":11},"description":"At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.\nDesignation DevSecOps & AI Engineer\nJob Description\nBuild and maintain secure CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, Azure DevOps, and CircleCI for application, data, and AI workloads.\nIntegrate DevSecOps practices into pipelines using Snyk, SonarQube, Checkmarx, Trivy, Anchore, and OWASP tools for continuous security scanning.\nImplement shift-left security with secret scanning (GitLeaks, TruffleHog), SBOM automation (Syft, CycloneDX), and dependency management (Dependabot, Renovate).\nWork with containerization (Docker/Podman) and Kubernetes (EKS, AKS, GKE) including Helm/Kustomize for deployments and secure image pipelines.\nDevelop and automate MLOps workflows using MLflow, Kubeflow, Azure ML, SageMaker, or Vertex AI for model training, packaging, and deployment.\nBuild and maintain RAG/AI integration pipelines using LangChain, LlamaIndex, Semantic Kernel, and vector databases like Pinecone, Weaviate, or FAISS.\nImplement AI inference systems using Seldon Core, KServe, BentoML, Ray Serve, or Triton Inference Server for scalable model serving.\nAutomate ETL/ELT and data feature pipelines using Airflow, Prefect, Dagster, dbt, or Kafka/Kinesis for AI model data feeds.\nWork with IaC tools such as Terraform, Pulumi, CloudFormation, or Azure Bicep to provision cloud and AI infrastructure.\nImplement event-driven architectures using serverless functions (AWS Lambda, Azure Functions, Cloud Functions) and messaging systems like Kafka or RabbitMQ.\nMaintain monitoring and logging using Prometheus, Grafana, ELK/Loki, OpenTelemetry, Jaeger, Datadog, or New Relic for both app and ML workloads.\nHandle model & data observability using tools like Evidently AI, Arize AI, WhyLabs, or Fiddler for drift, bias, and performance tracking.\nSecure cloud environments using IAM best practices (AWS IAM, Azure AD/Entra ID, GCP IAM), workload identities, and least-privilege controls.\nSupport configuration management using Ansible, Chef, or SaltStack for environment consistency and automation.\nDevelop scripts in Python, Bash, or SQL for automation, data processing, validation, and orchestration of ML workflows.\nImplement API integrations for AI systems using REST, gRPC, or GraphQL for model consumption and downstream applications.\nUse GitOps tools like Argo CD or Flux for automated, secure Kubernetes deployments and progressive delivery.\nApply AI security practices including guardrails, prompt protection, model validation, and safe inference techniques using industry tools.\nEnsure compliance with data governance, privacy, and security standards including GDPR, CCPA, and cloud security best practices.\nCollaborate with data engineers, ML engineers, DevOps teams, and security teams, contributing to documentation, reviews, and mentoring juniors.\nDesired Profile\nLooking for a DevSecOps & AI Engineer with 4-7 years of hands-on experience in cloud, DevOps, and AI/ML workflows.\nStrong skills in Terraform, Kubernetes, Helm, Docker, and CI/CD (GitHub Actions, GitLab CI, Jenkins, Azure DevOps).\nProficient in Python and scripting (Bash/PowerShell) with good automation mindset.\nExperience implementing DevSecOps practices-SAST/DAST, container scanning, secrets scanning, SBOM, and policy-as-code.\nExposure to MLOps/AI integration using MLflow, Kubeflow, SageMaker, Azure ML, KServe, or Seldon.\nFamiliar with cloud (AWS/Azure/GCP), configuration management (Ansible/Puppet), and GitOps tools (Argo CD/Flux).\nStrong communication, troubleshooting, and collaboration skills with ability to work cross-functionally.\nExperience : 4 to 7 years\nEducation : B.Tech. / BS in Computer Science\nTechnical Skills & Certifications\nTerraform, Pulumi, and Infrastructure as Code (IaC)\nKubernetes (EKS/AKS/GKE), Docker/Podman, Helm, Kustomize\nCI/CD tools: GitHub Actions, GitLab CI, Jenkins, Azure DevOps\nCloud platforms: AWS, Azure, GCP\nPython, Bash, PowerShell scripting\nDevSecOps tools: Snyk, SonarQube, Trivy, Checkmarx, GitLeaks, TruffleHog\nPolicy-as-code (OPA/Gatekeeper, Kyverno) and SBOM tools (Syft, CycloneDX)\nMLOps tools: MLflow, Kubeflow, SageMaker, Azure ML, Vertex AI\nModel serving frameworks: KServe, Seldon Core, BentoML, Ray Serve\nVector DBs & RAG stack: Pinecone, Weaviate, FAISS, Chroma, LangChain, LlamaIndex\nMonitoring & observability: Prometheus, Grafana, ELK/Loki, OpenTelemetry, Jaeger\nConfiguration management: Ansible, Puppet\nGitOps: Argo CD, Flux\nServerless: AWS Lambda, Azure Functions, Google Cloud Functions.\nEY | Building a better working world\nEY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.\nEnabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.\nWorking across assurance, consulting, law, strategy, tax and 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