Назад
3 дня назад

Chief Product and Technology Officer (AI)

Формат работы
hybrid
Тип работы
fulltime
Грейд
c_level
Страна
France
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Описание вакансии

TL;DR
Chief Product and Technology Officer (AI): Building AI-native internal infrastructure by centralizing company data, deploying a Google Cloud and BigQuery data lake, and integrating secure RAG architectures and AI agents with an accent on data engineering, governance, and cross-functional enablement. Focus on designing scalable pipelines, orchestrating document vectorization, securing access and confidentiality, and evolving agentic systems through user feedback.

Chief Product and Technology Officer

Company

Breega

Conditions

1 week ago

Skills

Candidate Availability

Required and preferred rules are kept separate and reflect the wording in the original posting.

About the Role

You will build an AI-native internal infrastructure from scratch. You will centralize company data, design and deploy a Google Cloud and BigQuery data lake, and build ETL/ELT pipelines. You will implement secure RAG architectures and AI agents, integrate them with existing tools, train users, establish governance, document processes, and maintain the technical stack.

Requirements

  • Seven or more years of experience as a senior freelance professional or independent consultant
  • Change management experience with non-technical teams
  • AI and LLM expertise, including RAG, embeddings, and agent orchestration
  • Data engineering experience with Python, BigQuery, SQL, and ETL/ELT pipelines
  • Google Cloud Platform and Google Workspace experience
  • Ability to design secure, scalable data architectures
  • CRM and AI-integration knowledge
  • Live AI or data project references

Responsibilities

  • Audit and centralize historical company data
  • Design and deploy a data lake on Google Cloud and BigQuery
  • Build ingestion, cleaning, and transformation pipelines
  • Orchestrate document vectorization
  • Deploy secure RAG architecture
  • Select embedding and generation models
  • Ensure data confidentiality and access segmentation
  • Design and deploy cross-functional and team-specific AI agents
  • Integrate agents with Affinity, Google Workspace, and Slack
  • Maintain and improve agents using user feedback
  • Run onboarding and training sessions
  • Prioritize high-return use cases and the roadmap
  • Document agentic processes and technical runbooks
  • Implement data governance, access control, versioning, audit trails, and GDPR compliance
  • Maintain and evolve the technical stack

Hiring Process

HR interview → interviews with partners → business case → final interviews with co-founders → two reference-check calls

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