Senior .NET AI Developer

Senior .NET AI Developer (Remote)

Job Summary:

We are looking for an experienced Senior .NET AI Developer to lead the design, development, and deployment of our AI-driven solutions and services using the Microsoft .NET ecosystem. This role involves establishing a robust in-house AI development pipeline and integrating cutting-edge generative AI capabilities into our .NET-based products. The ideal candidate will have over five years of experience in software development with at least three years focused on AI/ML integration, particularly within the .NET and Azure ecosystem.

As our Senior .NET AI Developer, you will be responsible for building and scaling AI applications that leverage large language models, Azure AI Services, and modern .NET frameworks. You will work closely with our product, data engineering, and DevOps teams to ensure these AI solutions are robust, scalable, and seamlessly integrated into our platform, while upholding security and quality standards for our startup's rapidly evolving offerings.

Key Responsibilities:

AI Solution Design & Integration: Lead the design, development, and integration of AI-driven solutions into our .NET applications using Azure AI Services, Semantic Kernel, and other Microsoft AI frameworks, ensuring these systems are robust, scalable, and deliver meaningful value to users.

Chatbot & Generative AI Applications: Build and integrate intelligent chatbot and generative AI applications using large language models (Azure OpenAI Service, OpenAI APIs) within .NET applications to enhance user engagement and automate customer support tasks.

Prompt Engineering & Workflow Orchestration: Design effective prompt engineering strategies and orchestrate multi-step AI agent workflows using Semantic Kernel, LangChain for .NET, or AutoGen to enable LLMs to perform complex tasks and conversations within .NET applications.

Data Pipelines & RAG Integration: Integrate vector databases (Azure AI Search, CosmosDB, Pinecone or similar) and implement retrieval-augmented generation (RAG) techniques to provide LLMs with relevant contextual data, working with data engineers to incorporate enterprise data sources (e.g., SQL Server, Azure SQL, Synapse) into AI pipelines.

Model Deployment & MLOps: Deploy and manage machine learning models (including LLMs and ML.NET models) in production on Azure cloud infrastructure, implementing MLOps best practices like CI/CD pipelines using Azure DevOps or GitHub Actions, containerization (Docker, Kubernetes/AKS), and automated testing to ensure reliable and scalable model deployments.

Performance Monitoring & Optimization: Monitor the performance of AI models and services using Azure Application Insights and other monitoring tools, recommend and implement optimizations (such as model fine-tuning, caching, or response streaming) to improve latency and accuracy, and troubleshoot any issues in the AI pipeline.

Scalability & Cost Optimization: Design AI systems with scalability and efficiency in mind using Azure's serverless offerings (Azure Functions, Container Apps) and optimize resource utilization and cloud costs for both model training and inference workloads.

Security & Compliance: Ensure AI solutions adhere to data privacy and security standards (e.g., GDPR) and implement appropriate access controls, managed identities, and governance to maintain compliance with organizational policies and ethical AI practices.

Collaboration: Work closely with product management, data engineering, DevOps, and software development teams to ensure AI initiatives align with business goals and integrate seamlessly into existing .NET workflows and applications.

Innovation & Best Practices: Stay up-to-date with the latest advancements in AI and machine learning within the Microsoft ecosystem (new Azure AI services, .NET libraries, techniques) and industry best practices. Drive continuous innovation and improvements in our AI solutions and development processes.

Required Skills & Qualifications:

Experience: Minimum of 5 years of experience in software development with .NET (C#), including at least 3 years of hands-on work integrating AI/ML capabilities into production .NET applications.

.NET Expertise: Strong proficiency in C# and .NET 8+, with experience building scalable applications using ASP.NET Core, and familiarity with modern .NET development patterns and practices.

LLM & NLP Integration: Deep understanding of how to integrate large language models into .NET applications, with hands-on experience using Azure OpenAI Service, OpenAI APIs, or similar LLM platforms within .NET solutions.

Azure AI Services: Proven experience with Azure AI Services including Azure OpenAI Service, Azure Cognitive Services (Language, Vision, Speech), and Azure AI Search for building intelligent applications.

Semantic Kernel & AI Orchestration: Hands-on experience with Microsoft Semantic Kernel for orchestrating AI workflows, managing plugins, and integrating LLMs into .NET applications. Familiarity with LangChain for .NET or similar frameworks is a plus.

Vector Databases & RAG: Practical experience with vector databases (Azure AI Search, CosmosDB or FAISS) and implementing retrieval-augmented generation techniques to provide relevant context to AI models within .NET applications.

ML.NET & Model Integration: Familiarity with ML.NET for building, training, and deploying machine learning models in .NET, and experience integrating pre-trained models (ONNX, TensorFlow, PyTorch models) into .NET applications where applicable.

MLOps & DevOps: Experience with Azure DevOps or GitHub Actions for building CI/CD pipelines for AI-enabled .NET applications, containerizing solutions with Docker, deploying to Azure Kubernetes Service (AKS), and implementing automated testing and monitoring.

Cloud Architecture: Strong experience deploying .NET applications on Microsoft Azure, leveraging services like Azure App Service, Azure Functions, Azure Container Apps, and Azure Kubernetes Service for scalability and performance.

Data Integration: Familiarity with Azure data services (Azure SQL Database, Cosmos DB, Azure Synapse, Azure Data Factory) and experience working with data engineering teams to ensure data quality, availability, and integration into AI pipelines.

Problem Solving: Strong analytical and troubleshooting skills for complex AI systems, with a proactive approach to identifying issues, debugging integration errors, and ensuring reliability of AI services in .NET applications.

Collaboration & Communication: Excellent communication skills and ability to work effectively in cross-functional teams. Able to articulate complex AI concepts in simple terms to non-technical stakeholders and collaborate on innovative solutions.

Nice-to-Have Qualifications:

Python & ML Frameworks: Familiarity with Python and machine learning frameworks (TensorFlow, PyTorch, scikit-learn) for understanding ML model development, model conversion (to ONNX), and collaborating with data science teams when needed.

Advanced Degree: Master's degree in Computer Science, Artificial Intelligence, or a related field, with any research publications or contributions to open-source AI projects.

Multi-Platform Development: Experience building cross-platform applications using .NET MAUI, Blazor, or other .NET frameworks that could benefit from AI integration.

Enterprise Integration: Experience with enterprise service bus patterns, microservices architecture, and integrating AI services into large-scale distributed .NET systems.

Monitoring & Observability: Hands-on experience with Azure Application Insights, Azure Monitor, and distributed tracing for tracking AI model performance, data drift, and system health in production environments.

AutoGen & Multi-Agent Systems: Familiarity with Microsoft AutoGen or similar frameworks for building multi-agent AI systems and complex AI-driven workflows.

What We Offer:

• Competitive salary and equity package
• Fully remote work environment with flexible hours
• Opportunity to work with cutting-edge AI technologies in the Microsoft ecosystem
• Collaborative startup culture with significant impact on product direction
• Professional development and learning opportunities
• Comprehensive benefits package

To Apply:

Please submit your resume along with examples of AI-enabled .NET applications you've built, GitHub profile, or portfolio demonstrating your experience with Azure AI Services and .NET AI integration.