GenAI Deployment Lead - Cloud AI Architect

MACHINE LEARNING TECHNOLOGIES LLC; Sunnyvale (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

To Be Discussed Later seeks an AI engineer to lead GenAI deployment efforts across customers, from discovery to delivery. The role requires deep Python, Langchain, LangGraph, and SQL experience, plus strong cloud proficiency (AWS/GCP/Azure) and architectural skills.

You will collaborate with product, ML, and engineering teams to shape the platform roadmap, write clean code, and build reusable deployment modules for scalable delivery.

Qualifications

• 10+ years of experience in software engineering or solutions engineering, ideally in a customer-facing capacity.
• Proven expertise in Python, Langchain, LangGraph, and SQL.
• Deep experience with engineering architecture, including APIs, microservices, and event-driven systems
• Demonstrated success in designing and deploying GenAI applications into production environments
• Strong proficiency with cloud services such as AWS, GCP, and/or Azure.
• Excellent communication skills, with the ability to translate technical complexity to customer-facing narratives.
• Comfortable working autonomously and managing multiple deployment tracks in parallel.

Responsibilities

• Lead the end-to-end deployment of GenAI applications for customers—from discovery to delivery.
• Architect and implement robust, scalable solutions using Python, Langchain/LangGraph, and LLM frameworks.
• Act as a trusted technical advisor to customers, understanding their needs and crafting tailored AI solutions.
• Collaborate closely with product, ML, and engineering teams to influence roadmap and core platform capabilities.
• Write clean, maintainable code and build reusable modules to streamline future deployments.
• Operate across cloud platforms (AWS, Azure, GCP) to ensure secure, performant infrastructure.
• Continuously improve deployment tools, pipelines, and methodologies to reduce time-to-value.

Skills

Python

Langchain

LangGraph

SQL

APIs

Microservices

Event-driven

AWS

GCP

Azure

GenAI deployment

Tools

Terraform

Pulumi

Docker

Kubernetes

Job description

To Be Discussed Later seeks an AI engineer to lead GenAI deployment efforts across customers, from discovery to delivery. The role requires deep Python, Langchain, LangGraph, and SQL experience, plus strong cloud proficiency (AWS/GCP/Azure) and architectural skills.

You will collaborate with product, ML, and engineering teams to shape the platform roadmap, write clean code, and build reusable deployment modules for scalable delivery.