GenAI Solutions Engineer — Enterprise AI & Agents

Madison-Davis; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Madison-Davis, LLC is seeking an experienced AI Engineer to design and deploy enterprise Generative AI applications and automation solutions. You will build secure, production-ready AI agents and integrate AI capabilities into existing enterprise apps, collaborating with both technical and non-technical stakeholders.

The role emphasizes hands-on Python engineering, building RAG solutions, and connecting AI workflows with databases and SaaS platforms. Strong communication skills are essential.

Qualifications

• 5–8 years of engineering experience.
• At least 2 years of enterprise GenAI or LLM development experience.
• Strong Python engineering skills.
• Experience implementing AI agents and workflows.
• Experience with enterprise integrations and APIs.
• Knowledge of prompt engineering, AI architecture, and model evaluation.

Responsibilities

• Design and deploy enterprise Generative AI applications.
• Develop autonomous and human-supervised AI agents.
• Build custom MCP servers, tools, and integrations.
• Create RAG applications using enterprise information sources.
• Develop Python services and APIs supporting AI-powered workflows.
• Connect AI solutions with enterprise applications, databases, and SaaS platforms.
• Implement security controls, governance, and data privacy safeguards.
• Optimize production AI applications for reliability, scalability, and performance.

Skills

Python

GenAI/LLM development

AI agents

APIs & SaaS connectivity

Communication

Problem-solving

Education

Bachelor's degree in a relevant technical field

Tools

Claude Code

Anthropic APIs

Azure AI Foundry

Azure OpenAI Service

Azure AI Search

MCP server

Job description

Madison-Davis, LLC is seeking an experienced AI Engineer to design and deploy enterprise Generative AI applications and automation solutions. You will build secure, production-ready AI agents and integrate AI capabilities into existing enterprise apps, collaborating with both technical and non-technical stakeholders.

The role emphasizes hands-on Python engineering, building RAG solutions, and connecting AI workflows with databases and SaaS platforms. Strong communication skills are essential.