AI Engineer with .Net.

Key Responsibilities

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.

AI Application Development

• 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.

Required Qualifications

• 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.

AI Experience

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.)

Experience with one or more of the following is preferred:

• Semantic Kernel

• LangGraph

• CrewAI

• AutoGen

• OpenAI Agents SDK

Working knowledge of:

• Model Context Protocol (MCP)

• Agent orchestration

• Tool calling

• AI workflow automation

Preferred Qualifications

• 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.