AI Engineer (.NET + GenAI)
Posted 1 week ago by Vedasoft Inc
Negotiable
Undetermined
Remote
Remote or Maryland
Summary: We are looking for an experienced AI Engineer with a robust .NET background to develop and scale intelligent applications focused on Generative AI and LLM integrations. The role involves leveraging Azure cloud services and modern data platforms to design enterprise-grade systems. The ideal candidate will have extensive experience in software development, particularly with C# and .NET technologies. This position is remote and offers a 6-month contract duration.
Key Responsibilities:
- Design and develop AI-powered applications using C#, .NET Core, and ASP.NET APIs
- Build and integrate LLM-based solutions using Azure OpenAI
- Implement Retrieval-Augmented Generation (RAG) using Azure AI Search
- Develop AI workflows using LangChain and LangGraph
- Build scalable, event-driven architectures using Kafka
- Integrate AI capabilities into microservices-based enterprise applications
- Work with structured and unstructured data using SQL and MongoDB
- Collaborate with data scientists and ML engineers to deploy models into production
- Develop secure, scalable APIs and backend systems
- Automate build, test, and deployment pipelines using CI/CD tools (Azure DevOps, GitHub Actions, etc.)
- Monitor and optimize AI model performance, latency, and cost
Key Skills:
- 7+ years of experience in software development with strong expertise in C# and .NET technologies
- Hands-on experience with Azure OpenAI (GPT models, embeddings, prompt engineering)
- Strong experience with Azure AI Search for RAG-based solutions
- Practical knowledge of LangChain and LangGraph frameworks
- Experience with event streaming platforms like Kafka
- Proficiency in MongoDB and SQL databases
- Experience building REST APIs and microservices architecture
- Strong understanding of CI/CD pipelines and DevOps practices
- Familiarity with cloud-native development on Microsoft Azure
- Good understanding of AI/ML concepts and NLP fundamentals
Salary (Rate): undetermined
City: undetermined
Country: undetermined
Working Arrangements: remote
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
Detailed Description From Employer:
Job Title: AI Engineer (.NET + GenAI)
Location: EST (Remote)
Duration: 6 months Contract
Role Overview:
We are seeking a highly experienced AI Engineer with a strong .NET background to build and scale next-generation intelligent applications. This role focuses on Generative AI, LLM integrations, and enterprise-grade system design, leveraging Azure cloud services and modern data platforms.
Key Responsibilities:
- Design and develop AI-powered applications using C#, .NET Core, and ASP.NET APIs
- Build and integrate LLM-based solutions using Azure OpenAI
- Implement Retrieval-Augmented Generation (RAG) using Azure AI Search
- Develop AI workflows using LangChain and LangGraph
- Build scalable, event-driven architectures using Kafka
- Integrate AI capabilities into microservices-based enterprise applications
- Work with structured and unstructured data using SQL and MongoDB
- Collaborate with data scientists and ML engineers to deploy models into production
- Develop secure, scalable APIs and backend systems
- Automate build, test, and deployment pipelines using CI/CD tools (Azure DevOps, GitHub Actions, etc.)
- Monitor and optimize AI model performance, latency, and cost
Required Skills & Qualifications:
- 7+ years of experience in software development with strong expertise in C# and .NET technologies
- Hands-on experience with Azure OpenAI (GPT models, embeddings, prompt engineering)
- Strong experience with Azure AI Search for RAG-based solutions
- Practical knowledge of LangChain and LangGraph frameworks
- Experience with event streaming platforms like Kafka
- Proficiency in MongoDB and SQL databases
- Experience building REST APIs and microservices architecture
- Strong understanding of CI/CD pipelines and DevOps practices
- Familiarity with cloud-native development on Microsoft Azure
- Good understanding of AI/ML concepts and NLP fundamentals