Senior Azure AI Platform Engineer

Encore GlobalSchiller Park, IL
1d

About The Position

The Senior Azure AI Platform Engineer is aligned with Encore’s Application Development Team to design, build, and operate scalable AI enabled platform capabilities on Microsoft Azure. This role focuses on creating the foundational services, patterns, and infrastructure that enable machine learning and generative AI features to be safely and effectively embedded across Encore’s applications. This position supports all phases of the product and platform lifecycle, from defining the right technical approach and standards to delivering, operating, and continuously improving production grade AI systems. Collaborating closely with software engineers, data partners, and product stakeholders, this role aims to translate business challenges into reliable, secure, and scalable AI powered solutions. The Senior Azure AI Platform Engineer reports to the Senior Manager of Applications Development.

Requirements

  • Bachelor’s degree in computer science, Engineering, or a related technical field, or equivalent practical experience
  • 6+ years of professional software engineering experience in enterprise, SaaS, or consulting environments
  • Proven experience designing, building, and supporting production-grade applications
  • Strong experience with C#, .NET, Web APIs, and modern backend development practices
  • Experience with Azure cloud services and cloud-native or serverless architectures
  • Familiarity with modern JavaScript frameworks; React or Next.js experience preferred
  • Experience working with relational and NoSQL databases such as SQL Server and Cosmos DB
  • Understanding of CI/CD pipelines, automated testing, and modern Git workflows
  • Strong communication skills with the ability to explain complex technical concepts clearly

Responsibilities

  • Lead the design and implementation of AI driven capabilities across Encore’s applications, embedding intelligence directly into workflows, user experiences, and backend services.
  • Partner with product managers and business stakeholders to identify where AI and machine learning can meaningfully improve decision making, automation, personalization, and operational efficiency.
  • Design and build reusable AI platform components, services, and patterns that application teams can safely and consistently adopt.
  • Apply generative AI, machine learning, and Azure AI services to real world business problems with a focus on reliability, security, and scalability.
  • Balance experimentation with production readiness, ensuring AI features are observable, testable, and maintainable.
  • Establish standards, guardrails, and best practices for AI usage across the application development organization.
  • Evaluate new Azure AI services and tooling, recommending adoption when clear business value exists.
  • Promote responsible AI practices including security, privacy, compliance, and cost awareness.
  • Support and improve production applications and AI-powered services.
  • Troubleshoot complex issues related to performance, reliability, and data quality.
  • Improve observability, monitoring, and operational maturity of AI and application services.
  • Identify opportunities to improve development workflows, automation, and deployment practices.
  • Create and maintain clear technical documentation covering architecture, AI patterns, and platform standards.
  • Enable application teams through documentation, shared services, and hands-on mentorship.
  • Contribute to a strong engineering culture focused on quality, ownership, and continuous improvement.
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