Senior Staff Engineer DevOps Engineer- AI/ML

Nagarro
Ajman, AE
RemoteCareer-pivot friendly

Why this role

Pace
Steady
Collaboration
Medium
Autonomy
Medium
Decision Impact
Team
Role Level
Individual Contributor
Career Pivot Friendly
Welcomes transferable skills

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • build and manage scalable automated infrastructure
  • implement and monitor MLOps workflows
Typical background
DevOps/MLOps experience

Transferable backgrounds

  • Coming from software
  • Coming from data-ai

Skills & requirements

Required

JenkinsGithub ActionsTerraformKubernetesDockerMlflow

Preferred

Llm/genai Deployment WorkflowsModel Performance Monitoring

Stack & domain

JenkinsGithub ActionsTerraformKubernetesDockerMlflowAzure MlBashPythonAIML

About the role

Original posting from Nagarro

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 optimisation best practices for ML infrastructure.

Remote Work

Yes

Employment Type

Full‑time

Source: Nagarro careers

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