Azure Machine Learning Customer Engineer

JDA TSG is seeking a forward-thinking Azure Machine Learning Expert to work as a Customer Engineer who thrives at the intersection of AI innovation, app development, and enterprise-scale delivery. In this customer-facing role, you’ll help customers leverage the Microsoft Azure AI ecosystem to build intelligent apps and production-ready AI agents.

Responsibilities:

• Facilitate AI strategy and implementation engagements, helping customers adopt and scale Azure Machine Learning, Azure AI Foundry, and Azure OpenAI services
• Provide clients guidance to architect and deploy intelligent agents and copilots using Copilot Studio, integrating custom business logic and APIs across enterprise workflows
• Guide customers in supporting end-to-end AI development lifecycles—from data ingestion and model training to fine-tuning, deployment, and monitoring
• Help clients’ developers and data scientists operationalize models and integrate them into real-time apps using CosmosDB as a scalable backend
• Educate customers on responsible AI, model lifecycle management, prompt engineering, vector search, and performance optimization
• Conduct workshops, demos, and working sessions to accelerate enterprise AI adoption and foster AI-first thinking across orgs
• Surface field feedback to Microsoft product teams and contribute to reusable IP, frameworks, and solution accelerators

Requirements:

• 10-15 years overall IT experience including 7 years experience in AI/ML engineering, app development, or cloud architecture roles
• Hands-on experience deploying LLM-based apps, building custom copilots, or fine-tuning OpenAI/GPT models
• Familiarity with Copilot Studio, Prompt Flow, and real-world applications of generative AI and agents
• Strong ability to connect AI innovation to business value, with experience leading technical conversations with devs, data scientists, and execs
• A 'builder's mindset' with a passion for helping customers turn vision into production-ready AI solutions
• AI & ML Platforms: Azure Machine Learning (AutoML, Prompt Flow, Responsible AI), Azure AI Foundry, Azure OpenAI (GPT, Codex, embeddings)
• Agent & Copilot Development: Building copilots with Copilot Studio, orchestrating agents via APIs, chaining models & workflows
• App Architecture: AI-infused web apps or chat interfaces powered by CosmosDB, Azure Functions, or App Service
• Data Engineering & Ops: Familiarity with data prep, vector embeddings, model tuning, and inference pipelines
• AI Governance: Prompt safety, cost control, performance tuning, and responsible AI practices
• Developer Experience: Guiding dev teams through prompt engineering, Copilot adoption, and AI integration workflows