Chief Product and Technology Officer
Breega is a venture capital firm backing exceptional founders from pre-Seed to Series A+ across Digital, Climate, and Deep Tech.
About Breega
Breega is a venture capital investor founded by former entrepreneurs and operators. The firm invests from pre-Seed through Series A+ in Digital, Climate, and Deep Tech startups, with offices in London and Paris and partners across Europe and Africa. Breega states that it manages €700 million and provides hands-on support in operations, talent, finance, marketing, sales, and portfolio scaling.
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
