Senior Staff Engineer (DevOps Engineer- AI/ML)

Nagarro; United Arab Emirates; Remote; AED 220,000 - 331,000; Full time

Job summary

A tech consulting firm in the United Arab Emirates is seeking a DevOps/MLOps Engineer. This role focuses on building and managing automated infrastructure for an LLM-powered GenAI platform. Responsibilities include designing CI/CD pipelines, automating infrastructure provisioning, and implementing MLOps workflows. Ideal candidates have strong experience with CI/CD tools, Kubernetes, Terraform, and scripting in Python and Bash. Full-time employment with remote work options is available.

Qualifications

• Hands-on experience with CI/CD tools like Jenkins or GitHub Actions.
• Proficiency with Terraform and Kubernetes.
• Strong scripting skills in Bash and Python.

Responsibilities

• Design and maintain CI/CD pipelines.
• Automate infrastructure provisioning using Terraform.
• Support deployment and monitoring of ML models in production.

Skills

Jenkins

GitHub Actions

Terraform

Kubernetes

Python

Bash

MLflow

cloud platforms

Tools

Docker

Azure

AWS

GCP

Job description

Job Description

Looking for a DevOps/MLOps Engineer to build and manage scalable automated infrastructure for our LLM-powered GenAI platform. You'll enable fast iteration and reliable deployment of models and services through robust CI/CD pipelines, container orchestration, and ML lifecycle tooling.

Key Responsibilities

• Design and maintain CI/CD pipelines using Jenkins, GitHub Actions, or similar.
• Automate infrastructure provisioning using Terraform and manage services with Kubernetes.
• Write and maintain Bash/Python scripts for automation and operational tooling.
• Implement and monitor MLOps workflows using tools like MLflow, Azure ML, or similar.
• Support deployment and monitoring of LLM-based models and APIs in production.

Required Skills

• Hands‑on experience with Jenkins, GitHub Actions, or equivalent CI/CD tools.
• Proficiency with Terraform, Kubernetes, Docker, and cloud‑native practices.
• Strong scripting skills in Bash and Python.
• Experience with ML model tracking, versioning, and deployment using MLflow or similar.
• Familiarity with cloud platforms (e.g., Azure, AWS, or GCP).

Nice to Have

• Exposure to LLM/GenAI deployment workflows.
• Experience with model performance monitoring and observability tools (Prometheus, Grafana, etc.).
• Security and cost optimization best practices for ML infrastructure.

Remote Work

Yes

Employment Type

Full‑time