Principal Solution Architect

AI EngineerKey Responsibilities As an AI Engineer, you will:Partner with business and technical stakeholders to identify and implement agentic AI and machine learning solutions that improve decision making, workflows, and automationDesign and implement cloud native AI architectures using Microsoft Azure services and established AI design patternsCollaborate with Data Scientists and other AI Engineers to transform prototypes into production ready, scalable solutionsBuild, deploy, and operate enterprise scale machine learning pipelines, emphasizing reliability, performance, and securityOrchestrate and configure infrastructure that enables low latency, resilient AI workloads, leveraging infrastructure as code and automationContribute to reusable accelerators, templates, and patterns that improve delivery speed and consistency across teamsSupport CI/CD, monitoring, and operational practices for AI and ML systems in production environmentsRequired Technical SkillsStrong experience with Microsoft Azure, including AI/ML services and cloud native architecturesHands on experience deploying and operating ML pipelines using Azure Machine LearningProficiency in Python and modern software engineering practicesExperience with automation and configuration management, including AnsibleSolid understanding of MLOps, model lifecycle management, and CI/CD for AI systemsExperience with containerization and orchestration technologies (e.g., Docker, Kubernetes)Working knowledge of security, identity, and access control in enterprise cloud environmentsPreferred SkillsExperience with Microsoft FoundryExperience implementing or operating agentic AI systemsFamiliarity with data engineering tools such as Databricks, Spark, Azure Data FactoryExperience integrating AI services (e.g., cognitive services, computer vision, unstructured data processing)Experience Requirements5+ years of experience in software engineering, AI engineering, or machine learning engineering rolesProven experience delivering production AI or ML solutions in a cloud environmentExperience collaborating with cross functional teams across data science, engineering, and architectureWays of WorkingAbility to work independently as a contractor while integrating effectively with existing teamsStrong communication skills, with the ability to explain complex technical concepts clearlyResults oriented mindset with a focus on delivering business value quickly and reliably