Azure Machine Learning Customer Engineer Job Listing at JDA TSG in United States of America (Job ID 1132)

Description

Overview

We're looking for a forward-thinking Azure Machine Learning Expert to works as a Customer Engineer (CE) who thrives at the intersection of AI innovation, app development, and enterprise-scale delivery. In this strategic role, you'll help customers leverage the Microsoft Azure AI ecosystem including Azure Machine Learning, Azure OpenAI, AI Foundry, and Copilot Studio to build intelligent apps, custom copilots, and production-ready AI agents.

This is a customer-facing role ideal for engineers who want to push the limits of what's possible with Generative AI, LLMs, and vector-powered applications using tools like CosmosDB.

• 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

Key Skills & Technologies:

• 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.

Ideal Candidate Will Have:

• 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.

At JDA TSG, our core values provide the framework that allows us to continually focus on what made us successful in the first place. Quite simply, our values inform everything that we do. We knew from day one that if we hired smart, passionate people and provided them meaningful yet challenging roles, we will thrive as an organization. We are excited to be here, doing meaningful work. 

We are committed to a diverse and inclusive workplace. We know diversity makes our team stronger, producing extraordinary results for our company and our clients. At JDA TSG, everyone is valued and empowered to succeed.

We are an equal opportunity employer committed to building an inclusive workplace. To view our Equal Employment Opportunity (EEO) policy, please click here.

Key Skills & Technologies:

• 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.

Ideal Candidate Will Have:

• 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.

• 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