Forward Deployment Engineer

t Studio, and plugin development.

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

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

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

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

• Build and optimize vector databases and semantic search using Azure AI Search for knowledge management systems.
  Design and develop scalable APIs and microservices for AI model deployment and integration.

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

• Define AI solution standards, best practices, and governance frameworks including security and compliance.
  Client Deployment & Collaboration .

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

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

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

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

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

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

Requirements

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

• 2+ years of comprehensive software engineering experience.

Technical Expertise

• Proven track record in architecting and implementing enterprise-scale AI 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 production environments.

• Deep expertise in Gen AI application development, including advanced prompt engineering, RAG architectures, fine-tuning strategies, and multi-agent orchestration.

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

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

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

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

• Deep understanding 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 technical concepts to both technical and non-technical stakeholders.

• Ability to adapt solutions to diverse client environments and data ecosystems.

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

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

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