Forward Deployment Engineer (FDE)
Office Based, Hyderabad Office
Cornerstone OnDemand is looking for a Forward Deployment Engineer (FDE) who will lead the design, development, and deployment of AI-powered solutions using Microsoft Azure AI services, Copilot, and Generative AI technologies. You will be responsible for building intelligent automation solutions, implementing AI models, and creating custom Gen AI applications - while working closely with client teams to ensure seamless integration and deployment within their environments.
In this role, you will... AI Solution Design & Development- Lead the development of enterprise AI solutions using Azure OpenAI, Azure AI Studio, Azure Machine Learning, and Azure Cognitive Services.
- Design and implement Microsoft Copilot solutions, including Copilot for Microsoft 365, custom copilots using Copilot 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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