Senior Software Developer(Full Stack) .Net with AI focus - Hybrid 3 days

Simple Solutions•Dallas, TX

9d•Hybrid

About The Position

We are seeking a highly skilled and forward-thinking Senior Software Engineer with over 9+ years of experience in designing and developing enterprise-grade solutions using .NET and C#, and at least 1-2 years of hands-on experience building AI solutions and intelligent agents on the Microsoft platform. The ideal candidate will be passionate about leveraging Prompt Engineering, Context Engineering, RAG, Vectorization & Indexing, and modern AI techniques to drive innovation and efficiency across our technology stack.

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
9+ years of experience in software development using .NET and C#.
1+ years of experience developing AI solutions and agents using Microsoft technologies.
Strong understanding of prompt engineering, context engineering, and LLM-based architectures.
Experience with RESTful APIs, microservices, and cloud-native development.
Familiarity with CI/CD pipelines, Git, and agile methodologies.
Excellent problem-solving, communication, and collaboration skills.

Nice To Haves

Experience with Azure OpenAI, Azure AI Foundry, Semantic Kernal Framework, AutoGen, Lang Graph, Machine Learning, or other Microsoft AI platforms.
Knowledge of NLP, generative AI, and conversational agent design.
Certifications in Microsoft Azure or AI-related technologies.
Contributions to open-source projects or technical blogs.

Responsibilities

Design, develop, and maintain scalable .NET/C# applications and services.
Design and implement AI-powered solutions using Microsoft Azure AI services, including Azure OpenAI, Azure AI Foundry, Cognitive Services and Microsoft Agent Framework.
Build and deploy intelligent agents that integrate with enterprise systems and workflows.
Apply prompt engineering and context engineering to optimize agent behavior and model outputs.
Integrate retrieval-augmented generation (RAG) pipelines to enhance agent knowledge and responsiveness.
Leverage tool use orchestration and action planning to enable agents to interact with external systems and APIs.
Implement memory management strategies for agents (episodic, semantic, and working memory).
Use state management, goal tracking, and feedback loops to support autonomous decision-making.
Evaluate and verify AI agents using various techniques and tools.
Collaborate with cross-functional teams including product managers, data scientists, and DevOps to deliver high-impact solutions.
Conduct code reviews, mentor junior engineers, and contribute to best practices in software development and AI integration.
Stay current with emerging technologies and trends in AI, machine learning, and software engineering.