Skill diminta
AWSAzureDockerGCPPlaywrightPython
Deskripsi
- AI Data Acquisition Engineer
- About Kulaa
- Kulaa is building an AI-powered food discovery and ordering platform.
We're looking for an exceptional engineer to build autonomous AI systems that continuously discover, extract, validate and enrich restaurant data at scale.
This is an initial contract role with the opportunity to transition into a permanent position for the right person.
Responsibilities
- Acquire restaurant data from Google Maps
- Build production-grade AI agents for autonomous data acquisition
- Design scalable browser automation and scraping systems
- Extract and structure restaurant, menu and business data
- Build automated data validation, enrichment and deduplication pipelines
- Integrate LLMs to improve data extraction accuracy
- Develop reliable systems that continuously monitor and update restaurant information
- Collaborate with our engineering team to build one of Kulaa's core competitive advantages
Requirements
- We're looking for someone with proven experience building production AI systems, including:
- AI agents
- Browser automation
- Large-scale web scraping
- LLM-powered data extraction
- Python
- Playwright (preferred)
- API integrations
- ETL and data pipelines
- Docker
- Cloud infrastructure (AWS, Azure or GCP)
Bonus experience
- Google Maps / Places
- OCR & vision models
- LangGraph, CrewAI, AutoGen or similar frameworks
- Marketplace or location datasets
- Knowledge graphs
- Proxy management & anti-bot techniques
- Contract → Permanent
This role will begin as a contract with clearly defined project milestones. Exceptional candidates will have the opportunity to transition into a permanent role and take ownership of Kulaa's AI-powered data acquisition platform.
- Next Steps
- Please submit your CV along with a cover letter.
- In your cover letter, please include
- dot points
covering
- AI agents you have built
- Autonomous systems you have built
- Relevant web scraping or browser automation projects
- Large-scale data acquisition experience
- LLM or AI-powered extraction systems
- The technologies and frameworks used
- The scale of each project (records, websites, users, etc.)
- Links to GitHub, live projects or portfolios (where available)
We're far more interested in what you've built than the number of years you've worked. Show us real systems you've shipped and the impact they had.