Forward Deployment Engineer

d plugindevelopment.

• Build advanced Gen AI applications using prompt engineering, RAG(Retrieval-Augmented Generation) patterns, fine-tuning, and multi-agentsystems.

• Develop intelligent workflows using Azure Agentic AI and SemanticKernel to automate complex business processes.

• Integrate AI capabilities with Microsoft 365, SharePoint, Teams, PowerPlatform, and third-party enterprise applications.

• Implement Azure AI Document Intelligence solutions for automateddocument processing and data extraction.

• Build and optimize vector databases and semantic search using Azure AISearch for knowledge management systems.

• Design and develop scalable APIs and microservices for AI modeldeployment and integration.

• Create data pipelines to support AI model training and real-timeinference.

• Define AI solution standards, best practices, and governanceframeworks including security and compliance.

ClientDeployment & Collaboration

• Participate in technical discovery sessions with client stakeholdersto understand business requirements and integration constraints.

• Support on-site and remote deployment of AI solutions within clientenvironments, managing configuration, data integration, and go-live activities.

• Deliver proof-of-concept projects to evaluate AI technologies anddemonstrate business value to client teams.

• Provide technical enablement and knowledge transfer sessions to clientengineering teams as needed.

• Gather client feedback to inform product improvements, working closelywith internal product and engineering teams.

**You've Got What It Takes If You Have...
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Requirements

• Bachelor's or master's degree in computer science, SoftwareEngineering.

• 2+ years of comprehensive software engineering experience.

Technical Expertise

• Proven track record in architecting and implementing enterprise-scaleAI solutions using Microsoft Azure AI services and Generative AI technologies.

• Expert-level experience with Azure OpenAI Service, Azure AI Studio,Azure Machine Learning, and Azure Cognitive Services in productionenvironments.

• Deep expertise in Gen AI application development, including advancedprompt engineering, RAG architectures, fine-tuning strategies, and multi-agentorchestration.

• Strong hands-on experience with Microsoft Copilot ecosystem, includingenterprise Copilot deployment, custom copilot development, plugin architecture,and extensibility frameworks.

• Advanced proficiency in Python and/or C# with deep knowledge of AI/MLframeworks.

• Expert-level understanding of LLM architectures, embeddings, andvector search technologies.

• Expertise in designing and implementing scalable API architectures,microservices patterns, and event-driven systems for AI solutions.

• Deepunderstanding of Azure AI Search, vector databases (Cosmos DB, Pinecone,Weaviate), and hybrid search optimization techniques.

Additional Skills

• Good communication skills with the ability to explain technicalconcepts to both technical and non-technical stakeholders.

• Ability to adapt solutions to diverse client environments and dataecosystems.

• Familiarity with enterprise security and compliance frameworks (SOC 2,GDPR, HIPAA) is a plus.

• Experience with multi-tenant SaaSdeployments and tenant-specific AI customization is a plus.

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