Description

You will design and implement agentic AI and machine learning architectures to automate workflows and improve decision making.

This role is on-site.

Responsibilities

• Design and implement cloud-native AI architectures using Microsoft Azure services and established design patterns.
• Transform prototypes into production-ready, scalable solutions in collaboration with Data Scientists and AI Engineers.
• Build, deploy, and operate enterprise-scale machine learning pipelines with a focus on reliability, performance, and security.
• Orchestrate infrastructure for low-latency, resilient AI workloads using infrastructure as code and automation.
• Support CI/CD, monitoring, and operational practices for AI and ML systems in production.

Required Skills

• 5+ years of experience in software engineering, AI engineering, or machine learning engineering.
• Strong experience with Microsoft Azure, including AI/ML services and cloud-native architectures.
• Hands-on experience deploying and operating ML pipelines using Azure Machine Learning.
• Proficiency in Python and modern software engineering practices.
• Experience with automation and configuration management, including Ansible.
• Solid understanding of MLOps, model lifecycle management, and CI/CD for AI systems.
• Experience with containerization and orchestration technologies such as Docker and Kubernetes.
• Working knowledge of security, identity, and access control in enterprise cloud environments.

Preferred Skills

• Experience with Microsoft Foundry or implementing agentic AI systems.
• Familiarity with data engineering tools including Databricks, Spark, and Azure Data Factory.

Key Skills

Education

Bachelor's degree