O

Onepoint

End-to-end organizational transformation and modernization

AI Engineer GCP

AI Application EngineeringUpdated on Nov 15
Full-timeNo salary listedIn-person

About the Job

Requirements

  • At least 3 years of experience in software development, data engineering, machine learning, or generative AI.
  • Significant experience implementing production solutions on Google Cloud Platform.
  • Experience with Vertex AI, Gemini, BigQuery, Cloud Run, and cloud-native GCP architectures.
  • Experience designing Retrieval-Augmented Generation (RAG) solutions, AI agents, and applications based on large language models (LLMs).
  • Good understanding of security, governance, and cost management in cloud environments.
  • Excellent command of Python and software development practices including Clean Code, Git, continuous integration and continuous delivery (CI/CD), automated testing, and code review.
  • Experience designing solutions using large language models (LLMs), orchestrating workflows with LangChain or LlamaIndex, and using Vertex AI, Gemini, Model Garden, and Vertex AI Agent Builder.
  • Proficiency with RAG architectures and related services such as BigQuery, Cloud Storage, AlloyDB, Vertex AI Vector Search, or other vector databases, depending on client needs.
  • Expertise in Google Cloud services including Cloud Run, Google Kubernetes Engine (GKE/Kubernetes), Vertex AI, Pub/Sub, Cloud Functions, Identity and Access Management (IAM), and Cloud Monitoring, as well as cloud architecture practices.
  • Experience implementing model deployment, evaluation, and monitoring pipelines using Vertex AI Pipelines, Vertex AI Evaluation, Model Monitoring, MLflow, or LangSmith.
  • Ability to integrate security mechanisms, data governance, and controls on AI usage to create reliable, compliant, and responsible solutions.

Responsibilities

  • Analyze business needs and design suitable generative AI solutions, including RAG, AI agents, prompt optimization, and model specialization when needed, using Google Cloud services.
  • Develop robust applications in Python and integrate AI models with existing systems through APIs, data pipelines, and cloud services, turning experiments into production solutions.
  • Deploy generative AI solutions on Google Cloud and ensure performance, scalability, security, observability, and cost control.
  • Explain technical issues to stakeholders and support business and IT teams in adopting generative AI use cases.
  • Work across the full project lifecycle, from consulting through coding.

Desired Qualifications

  • Google Professional Cloud Architect certification, Professional Machine Learning Engineer certification, or equivalent.
  • Experience with Vertex AI Agent Builder and multi-agent architectures.
  • Contributions to generative AI projects deployed in production.
  • Knowledge of Kubernetes environments, including GKE.

About the Company

Onepoint

End-to-end organizational transformation and modernization

Onepoint helps organizations modernize and transform by providing end-to-end advisory and delivery services that cover strategy, design, platforms, and implementation for both private sector companies and public administrations. It works by organizing its experts into open communities to combine business and technology skills, guiding projects from strategic vision through operational deployment across its global network of offices. The company differentiates itself through its open-community model, audacious and practical mindset, and its focus on designing concrete paths to the future—new ways of working, new business models, and new places—rather than just delivering isolated tech solutions. Its goal is to design a new world for its clients and help them move Beyond the obvious.

Company size
1,001-5,000
Company stage
Growth Equity (Non-Venture Capital)
Total funding
$176M
Headquarters
Paris, France
Founded
2002

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