GenAI Software Engineer: LLM & Agentic AI, Python Pro

Ethereum Technologies; New York (NY); On-site; USD 120,000 - 180,000; Full time

Job summary

Ethereum Technologies is seeking a strong AI Software Developer with 3–5 years of recent Python development experience. The role focuses on Generative AI and Agentic AI solutions, including LLM-powered applications, RAG, prompt engineering, NLP, and AI agents/workflows.

The candidate will collaborate with product managers, data engineers, data scientists, ML engineers, and business stakeholders to integrate AI capabilities into applications and workflows.

Qualifications

• 3–5 years of Python development experience required.
• Strong hands-on GenAI/LLM experience needed.
• Experience building production-quality software solutions.
• Candidate experience should justify submitted rate.
• Open to permanent employment without sponsorship.

Responsibilities

• Design, develop, test, and deploy production-quality software and AI applications.
• Develop GenAI and Agentic AI solutions using Python.
• Design, develop, test, and optimize prompts for Large Language Models.
• Build and integrate Retrieval-Augmented Generation (RAG) solutions.
• Develop AI agents and multi-agent workflows with Azure AI Foundry or CrewAI.
• Implement Agentic AI throughout the solution lifecycle.
• Apply Agentic AI design patterns (Tool Use, Reflection, Planning).
• Collaborate with product managers, data scientists, ML engineers, and stakeholders.
• Provide technical guidance and mentorship to junior team members.

Skills

Python

GenAI

LLM

Agentic AI

Production-ready software

Prompt engineering

Tools

Azure AI Foundry

CrewAI

Job description

Ethereum Technologies is seeking a strong AI Software Developer with 3–5 years of recent Python development experience. The role focuses on Generative AI and Agentic AI solutions, including LLM-powered applications, RAG, prompt engineering, NLP, and AI agents/workflows.

The candidate will collaborate with product managers, data engineers, data scientists, ML engineers, and business stakeholders to integrate AI capabilities into applications and workflows.