AI Cloud Devops Engineer

AI in Cloud Deployment, combining AI/ML expertise with cloud infrastructure and DevOps skills

Job Title: Devops Engineer

Location: Chennai

Job Type: Full-Time

Job Summary:

We are looking for a highly skilled AI Cloud Deployment Engineer to join our team to build, deploy, and scale AI/ML models and pipelines in cloud environments. The ideal candidate has strong experience with cloud platforms (Azure, AWS, GCP), containerization, CI/CD, and MLOps best practices. You will work closely with data scientists, ML engineers, and DevOps teams to operationalize AI solutions.

Key Responsibilities:

AI/ML models using Azure, AWS.

Set up CI/CD pipelines for continuous model integration and deployment (MLOps).

Monitor, troubleshoot, and optimize deployed AI services for performance and reliability.

Manage scalable data pipelines and APIs using cloud-native technologies.

Apply security best practices to model deployment and API access control.

Automate infrastructure provisioning with tools like Terraform or ARM templates.

Ensure reproducibility and versioning of ML experiments using tools like MLflow, DVC, or SageMaker.

Build dashboards and logging/monitoring systems for AI applications.

Required Skills

Hands-on experience in AI/ML model deployment in cloud environments (Azure ML, SageMaker, Vertex AI, etc.).

Proficiency in cloud computing: AWS, Azure, or GCP.

Experience with Docker, Kubernetes, and container orchestration.

MLOps

Familiarity with CI/CD tools: GitHub Actions, Jenkins, GitLab CI, or Azure DevOps.

Good programming skills in Python (FastAPI for serving models),Java .

Experience with infrastructure-as-code (Terraform, CloudFormation, Azure Bicep).

Knowledge of cloud security, networking, and identity management.

Preferred Qualifications:

Bachelors or Masters degree in Computer Science, Data Science, or related field.

Experience with ML tools like MLflow, Kubeflow, SageMaker Pipelines.

Knowledge of data engineering frameworks (Airflow, Kafka, Spark).

Prior experience working in Agile/Scrum environments.

Nice to Have:

Exposure to edge deployment for AI models (e.g., on IoT devices).

Knowledge of LLMOps and deploying generative AI models in production.

Familiarity with serverless compute services (AWS Lambda, Azure Functions).