AI Software Architect

5 days ago

Louisiana, United States Optomi Full time

AI Software Architect - GenAI / .NET 100% remote, based out of Louisiana Contract-to-Hire Convert at $185,000 - $215,000 + Bonus Optomi, in partnership with a consulting firm, is seeking an AI Software Architect. The AI Software Architect will design and lead the application-layer architecture for enterprise AI deployments across cloud platforms. Partnering closely with the NVIDIA Enterprise AI & Cloud Platforms team, this role translates business and AI requirements into intelligent software-based solutions integrated with Azure, AWS, and Google Cloud services. The ideal candidate brings a balance of software engineering maturity, AI innovation, and consulting acumen to deliver secure, scalable enterprise-grade applications. Architect and develop AI-enabled enterprise software solutions leveraging the .NET ecosystem (C#, ASP.NET Core, Entity Framework, Azure Functions, APIs). Design and implement retrieval-augmented generation (RAG), chatbot, and analytics interfaces that connect seamlessly to NVIDIA-backed AI infrastructure and cloud-native endpoints. Collaborate with hardware-focused AI consultants to bridge model orchestration layers with enterprise applications and APIs. Integrate NVIDIA Enterprise AI services, Azure Cognitive Services, AWS AI/ML tools, and Google Vertex AI within client solutions. Define best practices for AI-driven microservice architectures using containerized .NET Web APIs deployed to Kubernetes or cloud serverless environments. Lead code reviews, architectural assessments, and performance optimization of AI pipelines and application logic. Serve as a strategic advisor to clients, translating AI strategy and governance principles into technical roadmaps and actionable implementation plans. Contribute to internal innovation projects and reusable frameworks combining .NET and AI integration patterns. Required Skills & Qualifications Proven experience architecting and building scalable enterprise applications with the .NET stack (C#, ASP.NET Core, Web APIs, Entity Framework, Azure SDKs). Strong understanding of cloud-based software architecture, including hands-on experience with at least two of the following: Azure, AWS, Google Cloud. Practical experience integrating AI components (LLMs, vector databases, inference APIs) into enterprise application workflows. Experience configuring and deploying Kubernetes or container-based infrastructures for AI-enabled .NET services. Familiarity with NVIDIA Enterprise AI services (NIM, Triton, NeMo) and ability to operationalize them within application architectures.

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