AI Engineer with .Net
Job Description
Key Responsibilities
Software Engineering
Practical experience building AI-enabled applications using:
Software Engineering
- Design, develop, and maintain scalable enterprise applications using C#/.NET and ASP.NET Core.
- Build RESTful APIs, backend services, and microservices that power AI-enabled applications.
- Develop clean, maintainable, and production-ready software following engineering best practices.
- Collaborate with architects, product owners, and cross-functional engineering teams to deliver high-quality solutions.
- Engineer reusable components with a strong focus on scalability, reliability, performance, and security.
- Integrate internal and third-party platforms into Epiq's operational ecosystem.
- Utilize Azure DevOps for agile delivery, source control, CI/CD, and work management.
- Build AI-powered features using Python and modern LLM technologies.
- Develop intelligent agents that automate operational workflows and business processes.
- Design and implement Retrieval-Augmented Generation (RAG) solutions.
- Build and integrate Model Context Protocol (MCP) services and tools.
- Develop multi-agent workflows using modern agentic frameworks.
- Integrate enterprise applications with LLM services through APIs.
- Apply prompt engineering and AI evaluation techniques to improve solution quality.
- Modernize existing operational automations using AI-enabled architectures.
- 5+ years of professional software development experience.
- Strong hands-on experience developing enterprise applications using C#/.NET and ASP.NET Core.
- Proficiency in designing REST APIs and microservices.
- Experience with SQL Server or other relational databases.
- Strong understanding of object-oriented programming, software design patterns, and scalable system design.
- Experience with Git, Azure DevOps, CI/CD pipelines, and Docker.
Practical experience building AI-enabled applications using:
- Python
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- Vector databases and embeddings
- Prompt engineering
- AI API integrations (OpenAI, Azure OpenAI, Anthropic, Gemini, etc.)
- Semantic Kernel
- LangGraph
- CrewAI
- AutoGen
- OpenAI Agents SDK
- Model Context Protocol (MCP)
- Agent orchestration
- Tool calling
- AI workflow automation
- Experience with Microsoft Azure and Azure AI services.
- Azure OpenAI or Azure AI Foundry.
- Kubernetes and containerized deployments.
- Event-driven or distributed architectures.
- Enterprise workflow automation.
- Experience integrating AI capabilities into existing enterprise software products.
More Info
Key Skills
tool calling
object-oriented programming
Vector databases
AI API integrations
prompt engineering
scalable system design
ASP.NET Core
AI workflow automation
agent orchestration
About Company
Skills:
.Net Core, React, Spring Boot, Windows, Microservices, Nosql, Docker, Distributed Systems, Angular Js, Java, Sql, Linux, Azure, Kubernetes, AI system operations monitoring, cost-performance trade-offs, API SDK-based services, ChatGPT, AI ML basics, LLM usage patterns, AI-assisted development tools, responsible AI practices, enterprise compliance considerations, Messaging and event-driven architecture, Cloud platforms, REST Web APIs, GitHub Copilot
Skills:
.Net Core, React, SQL Server, Wcf, ASP.NET, Mvc, Angular, Web Services
Skills:
.NET, Reactjs, SQL Server, Microsoft Azure, AI Native Engineering, agentic implementations, Microsoft Azure Functions
Skills:
.NET, .Net Core, HTML, Microservices, Angular, React, Typescript, Azure Functions, Javascript, Azure DevOps, CSS, SQL Server, Rest Apis, Vector-based search, Prompt engineering, LLM integration, Azure Key Vault, Embeddings, Entity Framework ORM, Azure App Service, Azure AI Search, Azure OpenAI Service, ASP.NET Core Web API, AI application performance optimization, Azure Monitor