Azure Forward Deployment Engineer (Architect Level)

About the Role

As an Azure Forward Deployment Engineer (FDE), you will sit at the intersection of applied AI engineering and hands-on customer partnership. You will embed directly with our most strategic enterprise customers to design, prototype, and deliver production-grade AI solutions on Microsoft Azure—building agentic AI systems with Azure OpenAI Service, Azure AI Foundry, Semantic Kernel, and Microsoft Copilot technologies. You will write expert-level Python code and move fast enough to unblock customers in hours, not weeks.

This is not a pre-sales or support role. You are an L3-caliber software engineer and AI practitioner who works at the frontier of Microsoft’s AI ecosystem, transforming customer challenges into intelligent, scalable, enterprise-grade solutions.

Core Competencies

Every Azure FDE is expected to demonstrate mastery across four foundational competencies:

AI Engineering

Deep expertise in AI, Generative AI, and machine learning systems.

Full-Stack Delivery

End-to-end solution delivery from front-end through back-end systems.

Rapid Prototyping

Build and iterate on proofs of concept with exceptional speed.

Customer-Centric

Translate customer needs into precise, measurable technical solutions.

What You’ll Do

• Embed with enterprise customers to scope, architect, and deliver end-to-end AI solutions on Azure—from data ingestion through user-facing applications.
• Design and build agentic AI systems using Azure OpenAI Service, Azure AI Foundry, Semantic Kernel, LangChain, and Microsoft Copilot technologies, including multi-agent orchestration, memory, tool integration, retrieval-augmented generation (RAG), and autonomous workflows.
• Write expert-level Python code to develop, train, evaluate, and deploy machine learning models and Generative AI applications using Azure Machine Learning (Azure ML).
• Rapidly prototype customer solutions, solving technical blockers such as API integrations, custom connectors, document-processing workflows, and enterprise system integrations within tight timelines.
• Build full-stack solutions leveraging Azure OpenAI, Azure AI Search, Azure Functions, Azure App Service, Azure Container Apps, Azure Kubernetes Service (AKS), Event Grid, Service Bus, Cosmos DB, SQL Database, and Azure Data Lake.
• Lead customer discovery workshops to identify high-value AI use cases, assess data readiness, define success metrics, and align technical roadmaps.
• Implement MLOps best practices using Azure Machine Learning, GitHub Actions, Azure DevOps, model monitoring, feature stores, automated retraining, and CI/CD pipelines.
• Leverage Azure AI Services including Document Intelligence (Form Recognizer), Speech Services, Vision Services, Language Services, and Translator for accelerated AI solution delivery.
• Advise customers on Responsible AI, model governance, explainability, security, compliance, and Microsoft’s AI governance framework.
• Collaborate closely with Microsoft account teams, solution architects, and engineering organizations to accelerate customer outcomes.
• Produce architecture diagrams, technical design documents, deployment guides, operational runbooks, and executive presentations.
• Travel to customer locations as needed (typically up to 30%).

What We’re Looking For

Required Qualifications

• L3 Software Engineering Proficiency: Expert-level Python development skills including software architecture, design patterns, testing frameworks, debugging, optimization, and production-grade coding standards.
• Agentic AI Expertise: Hands-on experience building AI agents using Azure OpenAI, Semantic Kernel, Azure AI Foundry, LangChain, AutoGen, Microsoft Copilot Studio, or similar frameworks.
• Rapid Prototyping: Proven ability to solve ambiguous customer problems quickly by delivering working AI prototypes, integrations, and automation solutions.
• Full-Stack Development: Experience delivering complete solutions spanning data ingestion, AI/ML models, APIs, cloud services, and user-facing applications.
• 5+ years of professional software engineering experience, including at least 1 year delivering AI/ML solutions on Azure or another major cloud platform.
• Strong hands-on experience with:
  • Azure OpenAI Service
  • Azure Machine Learning
  • Azure AI Search
  • Azure AI Foundry
  • Azure Functions
  • Azure Container Apps or AKS
  • Azure Data Lake Storage
  • Cosmos DB
  • Azure SQL
• Strong understanding of Azure data services:
  • Azure Data Factory
  • Synapse Analytics
  • Event Hub
  • Service Bus
  • Data Lake Storage Gen2
• Familiarity with Azure infrastructure fundamentals:
  • Azure Active Directory (Entra ID)
  • Virtual Networks (VNet)
  • Managed Identities
  • Key Vault
  • Azure Monitor
  • Application Insights
• Excellent communication and stakeholder management skills, with the ability to explain complex AI systems to both technical and executive audiences.

Nice to Have

• Microsoft Certified: Azure AI Engineer Associate
• Microsoft Certified: Azure Solutions Architect Expert
• Microsoft Certified: Azure Data Scientist Associate
• Experience with GPT-4o, multimodal AI, speech, vision, document understanding, and video intelligence solutions.
• Background in NLP, conversational AI, computer vision, recommendation systems, or time-series forecasting.
• Experience with Semantic Kernel, AutoGen, CrewAI, LangGraph, or Microsoft Copilot Studio.
• Familiarity with Power BI, Microsoft Fabric, Synapse Analytics, or enterprise analytics platforms.
• Previous customer-facing consulting experience in AI Engineering, Data Science, Professional Services, or Cloud Transformation engagements.
• Knowledge of Responsible AI practices, model explainability techniques (SHAP, LIME), governance frameworks, and AI risk management.