GenAI Architect with GCP

Ethereum Technologies

Columbus (OH)

On-site

USD 170,000 - 260,000

Full time

12 hours ago
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Job summary

Ethereum Technologies is seeking an experienced GenAI Architect to design and implement scalable, secure GenAI solutions integrated into business applications and product platforms. You will lead end-to-end architecture for enterprise-grade GenAI, leveraging LLMs, embeddings, RAG, multi-agent systems, and responsible AI practices on GCP.

The role requires 6+ years in software or ML architecture, 2+ years with GenAI, and strong Python/Java skills, with a focus on enterprise governance and data

Qualifications

  • 6+ years of experience in Software Architecture, ML Engineering, Platform Engineering, or related fields.
  • 2+ years hands-on experience 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 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 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

Software architecture
ML engineering
Platform engineering
Python
Java
GCP
GenAI solutions
Governance
Data architecture

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.

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