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.