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).
