Generative AI Engineer

Micasa Global; United States; On-site; USD 180,000 - 240,000; Full time

Job summary

Micasa Global is hiring a Principal GenAI Engineer to lead enterprise GenAI initiatives for Fortune 500 clients. You will architect RAG-based solutions and scalable LLM deployments, driving production-grade AI products.

Applicants should have 8+ years in ML/AI systems and 2+ years with LLMs, with strong Python, LangGraph, SQL, and cloud experience across AWS, Azure, and GCP. You will mentor peers and own code quality in fast-moving projects.

Qualifications

• 8+ years of experience in ML/AI systems.
• 2+ years hands-on experience with LLMs (RAG, agents, prompt engineering).
• Strong proficiency in Python, LangGraph, and SQL.
• Experience deploying GenAI systems on AWS / Azure / GCP.
• Develop and optimize LLM-based solutions: prompt engineering, retrieval‑augmented generation (RAG), and agent‑based architectures.
• Codebase ownership: Python (LangChain/LangGraph) and SQL, focusing on reusable components, scalability, and performance.
• Cloud integration: deployment on Azure, GCP, or AWS with robust CI/CD processes.
• Cross‑functional collaboration with product owners, data scientists, and business SMEs.

Responsibilities

• Lead the design and deployment of large language models.
• Build scalable, production-grade GenAI applications.
• Mentor engineers and share ML best practices.
• Collaborate with product and data science teams to define requirements.
• Ensure robust CI/CD and cloud deployment practices.

Skills

Python

LangGraph

SQL

LangChain

AWS

Azure

GCP

Tools

LangChain

CI/CD

Job description

Client is hiring a Principal GenAI Engineer with strong expertise in LLMs to lead enterprise-scale AI implementations for Fortune 500 clients. This role focuses on building RAG systems that combine structured semantic reasoning with advanced LLM architectures to deliver scalable, explainable, production-grade AI solutions.

What We’re Looking For

• 8+years of experience in ML/AI systems
• 2+ years hands‑on experience with LLMs (RAG, agents, prompt engineering)
• Strong proficiency in Python, LangGraph, and SQL
• Experience deploying GenAI systems on AWS / Azure / GCP
• Develop and optimize LLM-based solutions: Lead the design and deployment of large language models, leveraging techniques like prompt engineering, retrieval‑augmented generation (RAG), and agent‑based architectures.
• Codebase ownership: Build and maintain/review high‑quality, efficient code in Python (using frameworks like LangChain/LangGraph) and SQL, focusing on reusable components, scalability, and performance best practices.
• Cloud integration: Aide in deployment of GenAI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI/CD processes.
• Cross‑functional collaboration: Work closely with product owners, data scientists, and business SMEs to define project requirements, translate technical details, and deliver impactful AI products.
• Mentoring and guidance: Provide technical leadership and knowledge‑sharing to the engineering team, fostering best practices in machine learning and large language model development.