AI Full-Stack Software Developer

Jefferson Capital Systems•Sartell, MN

About The Position

Design, develop, and maintain modern full-stack applications and reusable software components, APIs, services, and frameworks for enterprise application development. Build and integrate AI solutions, including Generative AI, Retrieval-Augmented Generation (RAG), machine learning services, and intelligent automation. Develop secure, scalable REST APIs, microservices, and front-end experiences that support AI-powered business applications and features such as conversational AI, intelligent recommendations, predictive analytics, and automation workflows. Integrate enterprise data sources with AI platforms, vector databases, and cloud-based AI services. Collaborate with business stakeholders, product owners, and cross-functional teams to identify opportunities for AI to improve operational efficiency, customer experiences, and decision-making. Optimize application performance, scalability, reliability, and security across distributed systems; participate in architecture and code reviews and technology evaluations; develop CI/CD pipelines and deployment automation; and implement testing, monitoring, logging, and observability for production applications. Stay current with emerging AI technologies, development frameworks, cloud services, and software engineering practices. Contribute to enterprise AI governance, security, data privacy, and responsible AI initiatives.

Requirements

Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related field, or equivalent experience.
At least 5 years of professional software development experience using C# and the .NET platform.
Strong experience developing modern web applications with ASP.NET Core, Web APIs, and front-end frameworks such as React, Angular, or Blazor.
Experience designing reusable software components and enterprise application architectures.
Knowledge of AI and machine learning concepts, including LLMs, prompt engineering, vector databases, embeddings, and AI orchestration frameworks.
Experience integrating AI platforms such as Azure OpenAI, Microsoft Copilot Studio, Azure AI Services, OpenAI APIs, Anthropic Claude APIs, or similar platforms.
Strong understanding of relational and non-relational databases, including SQL Server, PostgreSQL, Cosmos DB, or similar platforms.
Experience with source control systems such as Git and collaborative development workflows.
Understanding of object-oriented programming principles, software design patterns, and secure coding practices.
Strong troubleshooting, analytical, and problem-solving capabilities.
Self-motivated and able to complete tasks with little direct supervision or assistance.
Able to contribute to a team-oriented, collaborative environment.
Passionate about learning, embracing new technologies, and solving complex business challenges.

Nice To Haves

Experience with Azure AI Foundry, Azure OpenAI, Microsoft Copilot Studio, Semantic Kernel, LangChain, or similar AI development frameworks.
Experience developing RAG solutions.
Experience with Kubernetes, containers, and cloud-native application architectures.
Knowledge of DevOps practices, CI/CD pipelines, Infrastructure as Code, GitHub Actions, or Azure DevOps.
Experience with vector databases such as Pinecone, Azure AI Search, Weaviate, or Qdrant.
Familiarity with MLOps concepts and machine learning deployment pipelines.
Experience building AI agents, workflow automation, and autonomous business process solutions.
Knowledge of information security, AI governance, and secure development lifecycle practices.
Experience with financial services, collections, fintech, or other regulated industries.
Microsoft Azure, AI, or cloud certifications.

Responsibilities

Design, develop, and maintain modern full-stack applications using C#, .NET, ASP.NET Core, React, Angular, Blazor, and related technologies.
Build reusable software components, APIs, services, and frameworks that accelerate enterprise application development.
Develop and integrate AI solutions, including Generative AI, RAG, machine learning services, and intelligent automation capabilities.
Create secure and scalable REST APIs and microservices for AI-powered business applications.
Collaborate with business stakeholders, product owners, and cross-functional teams to identify AI opportunities.
Develop front-end experiences incorporating conversational AI, intelligent recommendations, predictive analytics, and automation workflows.
Integrate enterprise data sources with AI platforms, vector databases, and cloud-based AI services.
Optimize performance, scalability, reliability, and security across distributed systems.
Participate in architecture reviews, code reviews, and technology evaluations.
Develop and maintain CI/CD pipelines and deployment automation processes.
Implement testing strategies, monitoring, logging, and observability for production applications.
Keep current with emerging AI technologies, development frameworks, cloud services, and software engineering best practices.
Contribute to enterprise AI governance, security, data privacy, and responsible AI initiatives.