Ai & Llm Engineer

Dxc; Dadri; On-site; INR 3,000,000 - 5,000,000; Full time

Job summary

EY in India is seeking a DevSecOps & AI Engineer to design and maintain secure CI/CD pipelines for applications, data and AI workloads. You will integrate SAST/DAST, SBOM automation, and secret scanning across the stack while advancing MLOps workflows for model training, packaging, and deployment.

The role requires 4–7 years of hands-on experience, strong Terraform/Kubernetes/Docker skills, and proficiency in cloud platforms (AWS/Azure/GCP). You will collaborate跨

Qualifications

• 4–7 years hands-on cloud, DevOps and AI/ML workflows.
• Proficient in Terraform, Kubernetes, Helm, Docker and CI/CD (GitHub Actions, GitLab CI, Jenkins, Azure DevOps).
• Experience implementing DevSecOps—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.
• Familiar with cloud AWS/Azure/GCP, configuration management (Ansible/Puppet) and GitOps tools (Argo CD/Flux).
• Strong communication and cross-functional collaboration skills.

Responsibilities

• Build and maintain secure CI/CD pipelines using multiple tools for apps, data and AI workloads.
• Integrate DevSecOps practices with security scanning and SBOM automation.
• Develop MLOps workflows for model training, packaging and deployment.
• Create RAG/AI integration pipelines and scalable AI inference systems.
• Automate ETL/ELT and data feature pipelines for AI model data feeds.
• Provision cloud/AI infra with IaC (Terraform, Pulumi, CloudFormation).
• Implement event-driven architectures and serverless components.
• Monitor and observe apps and ML workloads with Prometheus, Grafana, OpenTelemetry, etc.
• Ensure data governance, privacy and security compliance.
• Collaborate with data/ML, DevOps and security teams; contribute to documentation and mentoring.

Skills

Terraform

Kubernetes

Docker

Helm

CI/CD

GitHub Actions

GitLab CI

Jenkins

Azure DevOps

AWS

Azure

GCP

Snyk

SonarQube

Trivy

Checkmarx

GitLeaks

TruffleHog

Syft

CycloneDX

MLflow

Kubeflow

SageMaker

Azure ML

Vertex AI

KServe

Seldon Core

BentoML

Ray Serve

Pinecone

Weaviate

FAISS

Chroma

LangChain

LlamaIndex

Prometheus

Grafana

OpenTelemetry

Jaeger

Ansible

Puppet

Argo CD

Flux

AWS Lambda

Azure Functions

Google Cloud Functions

Education

B.Tech./BS in Computer Science

Tools

Terraform

Kubernetes

Docker

Helm

GitHub Actions

GitLab CI

Jenkins

Azure DevOps

AWS

Azure

GCP

Snyk

SonarQube

Trivy

Checkmarx

TruffleHog

Job description

Designation DevSecOps & AI Engineer

Job Description

• 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.

Desired Profile

Looking for a DevSecOps & AI Engineer with 4-7 years of hands-on 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 practices—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. 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 cross-functionally. Experience : 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.

EY | Building a better working world EY 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. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.