Generative AI Architect

Machine Learning Technologies, LLC; Plano (TX); On-site; USD 150,000 - 210,000; Full time

Job summary

Machine Learning Technologies, LLC is seeking a senior AI Architect to design and implement end-to-end Generative AI and Agentic AI solutions for large-scale production environments in Plano, Texas.

You will lead deployment from POC to production, shape enterprise-grade architectures, and ensure security, governance, and reliable integration with cloud services and data platforms.

Qualifications

• 8–10+ years of experience in software engineering, data science, ML, or AI.
• 3+ years as a solution architect/system architect.
• Proven GenAI deployments at large-scale production.
• Hands-on with Generative AI, LLMs, RAG, and multi-agent architectures.
• Strong programming in Python.
• Experience with LangChain, LlamaIndex, CrewAI, or AutoGen.
• Cloud architecture experience with Azure or GCP.
• Experience with vector databases (e.g., Pinecone, Milvus, Qdrant, PGVector).
• Understanding of MLOps/LLMOps, deployment and monitoring.
• Experience with SQL, PySpark, distributed computing, or API design.
• Experience with PyTorch or TensorFlow.

Responsibilities

• Architect and implement end-to-end Generative AI and Agentic AI solutions.
• Design enterprise-grade solutions using LLMs, RAG, multi-agent workflows, and vector databases.
• Build scalable AI architectures on Microsoft Azure or Google Cloud Platform.
• Lead GenAI solutions from POC through production deployment.
• Integrate GenAI solutions with enterprise apps, APIs, data platforms, and cloud services.
• Establish MLOps/LLMOps for deployment, monitoring, and lifecycle management.
• Design solutions considering security, scalability, governance, reliability, and integration requirements.

Skills

Senior experience

Solution Architect

GenAI deployments

Python

LangChain

Cloud: Azure/GCP

Vector databases

MLOps/LLMOps

SQL PySpark

PyTorch/TensorFlow

Tools

LangChain

LlamaIndex

CrewAI

AutoGen

Job description

Job Description

• Architect and implement end-to-end Generative AI and Agentic AI solutions.
• Design enterprise-grade solutions using LLMs, RAG, multi-agent workflows, and vector databases.
• Build scalable AI architectures on Microsoft Azure or Google Cloud Platform (GCP).
• Lead GenAI solutions from POC/prototype through production deployment.
• Integrate GenAI solutions with enterprise applications, APIs, data platforms, and cloud services.
• Establish MLOps/LLMOps practices for deployment, monitoring, and lifecycle management
• Design solutions considering enterprise security, scalability, governance, reliability, and integration requirements.

Must-Have Skills

• 8–10+ years of experience in Software Engineering, Data Science, Machine Learning, or AI
• 3+ years of experience as a Solution Architect/System Architect.
• Strong enterprise-level experience architecting and deploying GenAI solutions in large-scale production environments.
• Hands-on experience with Generative AI, LLMs, RAG, and Agentic AI/Multi-Agent architectures.
• Strong programming experience in Python.
• Experience with LangChain, LlamaIndex, CrewAI, AutoGen, or similar frameworks.
• Strong cloud architecture experience with Microsoft Azure or GCP.
• Hands-on experience with vector databases such as Pinecone, Milvus, Qdrant, or PGVector
• Strong understanding of MLOps/LLMOps, model deployment, monitoring, and productionization.
• Experience with SQL, PySpark, distributed computing, and API design.
• Experience with PyTorch or TensorFlow.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.