GenAI Architect with GCP

Quantum Technologies. LLC; Columbus (OH); On-site; USD 140,000 - 210,000; Full time

Job summary

Quantum Technologies. LLC seeks an experienced GenAI Architect to design and implement scalable, secure enterprise GenAI solutions integrated into product platforms.

You will lead end-to-end architecture for GenAI applications, using LLMs, embeddings, and RAG architectures, while ensuring governance, security, and cost efficiency. The role requires strong GCP proficiency, experience with AI governance, and ability to guide engineering teams on GenAI development and integration across

Qualifications

• 6+ years of experience in Software Architecture, ML Engineering, Platform Engineering, or related fields.
• 2+ years of hands-on experience working with AI/ML systems, including Generative AI.
• Strong programming experience in Python, Java, or similar languages.
• Strong hands-on experience with Google Cloud Platform (GCP).
• Experience designing and implementing enterprise-grade GenAI solutions.
• Experience with enterprise AI governance or regulated industry environments.
• Familiarity with open-source AI ecosystems and foundation models.
• Background in data platforms, analytics engineering, or data architecture.

Responsibilities

• Design and own end-to-end architecture for enterprise-grade Generative AI applications and product features.
• Architect and implement GenAI solutions using Large Language Models (LLMs), foundation models, embeddings, and multimodal AI.
• Design and develop Retrieval-Augmented Generation (RAG) architectures and enterprise knowledge retrieval systems.
• Implement AI agents, multi-agent systems, prompt engineering, and workflow orchestration.
• Integrate GenAI capabilities into customer-facing and internal enterprise applications.
• Define reusable architecture patterns, standards, and best practices for prompts, agents, and inference services.
• Design scalable, modular, and low-latency AI architectures with model routing and fallback strategies.
• Guide engineering teams on GenAI development, implementation, and integration.
• Build and optimize data pipelines, document ingestion, chunking, embeddings, and vector search solutions.
• Implement MLOps practices, including model versioning, deployment, monitoring, logging, and performance optimization.
• Leverage GCP cloud services to build, deploy, and manage production-ready AI solutions.
• Implement AI security controls, guardrails, content filtering, and responsible AI practices.
• Ensure data privacy, governance, compliance, and security across GenAI solutions.
• Optimize model inference, application performance, scalability, and cloud infrastructure costs.

Skills

GenAI Architect

GCP

ML Engineering

Enterprise Architecture

Python/Java

LLMs & embeddings

MLOps

Tools

LLMs

Vector databases

RAG architectures

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Work Authorization:US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other

Job Description:

We are seeking an experienced GenAI Architect with strong expertise in Generative AI, Google Cloud Platform (GCP), Machine Learning, and enterprise architecture. The ideal candidate will be responsible for designing and implementing scalable, secure, and enterprise-grade GenAI solutions integrated into business applications and product platforms..

• Design and own end-to-end architecture for enterprise-grade Generative AI applications and product features.
• Architect and implement GenAI solutions using Large Language Models (LLMs), foundation models, embeddings, and multimodal AI.
• Design and develop Retrieval-Augmented Generation (RAG) architectures and enterprise knowledge retrieval systems.
• Implement AI agents, multi-agent systems, prompt engineering, and workflow orchestration.
• Integrate GenAI capabilities into customer-facing and internal enterprise applications.
• Define reusable architecture patterns, standards, and best practices for prompts, agents, and inference services.
• Design scalable, modular, and low-latency AI architectures with model routing and fallback strategies.
• Guide engineering teams on GenAI development, implementation, and integration.
• Build and optimize data pipelines, document ingestion, chunking, embeddings, and vector search solutions.
• Implement MLOps practices, including model versioning, deployment, monitoring, logging, and performance optimization.
• Leverage GCP cloud services to build, deploy, and manage production-ready AI solutions.
• Implement AI security controls, guardrails, content filtering, and responsible AI practices.
• Ensure data privacy, governance, compliance, and security across GenAI solutions.
• Optimize model inference, application performance, scalability, and cloud infrastructure costs.

Required Qualifications:

• 6+ years of experience in Software Architecture, ML Engineering, Platform Engineering, or related fields.
• 2+ years of hands-on experience working with AI/ML systems, including Generative AI.
• Strong programming experience in Python, Java, or similar languages.
• Strong hands-on experience with Google Cloud Platform (GCP).
• Experience designing and implementing enterprise-grade GenAI solutions.
• Experience with enterprise AI governance or regulated industry environments.
• Familiarity with open-source AI ecosystems and foundation models.
• Background in data platforms, analytics engineering, or data architecture.

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.