Generative AI Architect

Nexwave; Plano (TX); Presencial; USD 180.000 - 260.000; Jornada completa

Descripción de la vacante

Nexwave is seeking an experienced Generative AI Architect to design and implement enterprise-scale GenAI solutions in Plano, Texas. The role focuses on architecting end-to-end GenAI and Agentic AI systems, leveraging LLMs, RAG, and multi-agent workflows, with production deployments on Azure or GCP.

The candidate will drive POC-to-production efforts, integrate with enterprise APIs and data platforms, and establish MLOps/LLMOps to ensure governance, security, and reliability across scalable

Formación

• 8-10+ years in Software Engineering, Data Science, ML, or AI.
• 3+ years as a Solution Architect/System Architect.
• Proven GenAI deployments at enterprise scale.
• Strong Python programming experience.

Responsabilidades

• Architect end-to-end Generative AI and Agentic AI solutions.
• Design enterprise-grade AI using LLMs, RAG, and multi-agent systems.
• Build scalable AI architectures on Azure or GCP.
• Lead GenAI projects from POC to production deployment.
• Integrate GenAI with enterprise apps, data platforms, and APIs.
• Establish MLOps/LLMOps practices for deployment and monitoring.
• Address security, scalability, governance, and reliability.

Conocimientos

Software Engineering

Data Science

Machine Learning

AI

Solution Architect

GenAI & LLMs

Python

Azure & GCP

Vector Databases

MLOps/LLMOps

SQL / PySpark

Herramientas

LangChain

LlamaIndex

CrewAI

AutoGen

Descripción del empleo

We are looking for an experienced and hands-on Generative AI (GenAI) Architect to design and implement enterprise-scale AI solutions. The ideal candidate will have strong experience with LLMs, Agentic AI, RAG, MLOps/LLMOps, cloud architecture, and enterprise production deployments.

The candidate must have proven experience taking GenAI solutions from prototype/POC to scalable enterprise production environments.

Key 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 (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.