GenAI Deployment Lead | Cloud AI Solutions Architect

Quantum Technologies. LLC; Sunnyvale (TX); On-site; USD 180,000 - 240,000; Full time

Job summary

Quantum Technologies. LLC in the United States seeks a senior GenAI Deployment Lead to guide end-to-end customer solutions, from discovery to delivery. You will architect scalable systems using Python, Langchain/LangGraph, and modern LLM frameworks across AWS, Azure, and GCP.

You’ll collaborate with product, ML and engineering teams to shape roadmaps, write clean reusable code, and accelerate time-to-value. Exceptional communication and 10+ years in software/solutions engineering are essential.

Qualifications

• 10+ years of experience in software/solutions engineering, preferably customer-facing.
• Proven Python, Langchain, LangGraph, SQL expertise.
• Deep experience with engineering architecture, APIs, microservices, events.
• Experience designing and deploying GenAI applications into production.
• Strong cloud proficiency (AWS, GCP, Azure).
• Excellent communication translating tech to customers.

Responsibilities

• Lead end-to-end GenAI deployments from discovery to delivery.
• Architect scalable solutions using Python, Langchain/LangGraph, and LLMs.
• Act as trusted technical advisor to customers and tailor AI solutions.
• Collaborate with product, ML, and engineering to influence roadmap.
• Write clean, reusable code and deployable modules.
• Operate across AWS/Azure/GCP to ensure secure infra.
• Improve deployment tools and pipelines to reduce time-to-value.

Skills

10+ years experience in software/solns

Python

Langchain

LangGraph

SQL

Engineering architecture

GenAI deployments

Cloud services (AWS/GCP/Azure)

Communication skills

Tools

Docker

Kubernetes

Terraform

Pulumi

Job description

Quantum Technologies. LLC in the United States seeks a senior GenAI Deployment Lead to guide end-to-end customer solutions, from discovery to delivery. You will architect scalable systems using Python, Langchain/LangGraph, and modern LLM frameworks across AWS, Azure, and GCP.

You’ll collaborate with product, ML and engineering teams to shape roadmaps, write clean reusable code, and accelerate time-to-value. Exceptional communication and 10+ years in software/solutions engineering are essential.