Responsibilities:

Partner with business and technical stakeholders to identify and implement agentic AI and machine learning solutions that improve decision making, workflows, and automation.
Design and implement cloud native AI architectures using Microsoft Azure services and established AI design patterns.
Collaborate with Data Scientists and other AI Engineers to transform prototypes into production ready, scalable solutions.
Build, deploy, and operate enterprise scale machine learning pipelines, emphasizing reliability, performance, and security.
Orchestrate and configure infrastructure that enables low latency, resilient AI workloads, leveraging infrastructure as code and automation.
Contribute to reusable accelerators, templates, and patterns that improve delivery speed and consistency across teams.
Support CI/CD, monitoring, and operational practices for AI and ML systems in production environments.

Required Technical Skills:

Strong experience with Microsoft Azure, including AI/ML services and cloud native architecture.
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 (e.g., Docker, Kubernetes).
Working knowledge of security, identity, and access control in enterprise cloud environments.

Experience Requirements:

5+ years of experience in software engineering, AI engineering, or machine learning engineering roles.
Proven experience delivering production AI or ML solutions in a cloud environment.
Experience collaborating with cross functional teams across data science, engineering, and architecture.
Ability to work independently as a contractor while integrating effectively with existing teams.
Strong communication skills, with the ability to explain complex technical concepts clearly.
Results oriented mindset with a focus on delivering business value quickly and reliably.

Preferred Skills

Experience with Microsoft Foundry
Experience implementing or operating agentic AI systems.
Familiarity with data engineering tools such as Databricks, Spark, Azure Data Factory.
Experience integrating AI services (e.g., cognitive services, computer vision, unstructured data processing).

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