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