Remote Software Engineer, Data Growth & Automation
chainlink-labs
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Job summary
Chainlink Labs is seeking a Software Engineer in Data Growth to build scalable automation and self-service experiences that streamline customer onboarding and product adoption. You will apply AI-enabled solutions and systems thinking to improve efficiency across growth-related processes.
The role emphasizes collaboration across technical and business teams to solve complex problems and deliver measurable improvements in onboarding cycle times and data provisioning.
Qualifications
- Experience building software products or platforms with modern web technologies.
- Experience leveraging AI tools or frameworks to improve products or workflows.
- Exposure to Web3 technologies, ecosystems, or decentralized apps, or electronic trading environments.
- Strong systems-thinking capabilities to understand complex processes and architectures.
Responsibilities
- Design and build automation capabilities that reduce manual effort across customer onboarding and operational workflows.
- Develop self-service experiences enabling customers to onboard, configure, and access products with minimal human intervention.
- Improve customer growth outcomes by reducing onboarding cycle times and increasing process scalability.
- Re-architect systems and workflows to support provisioning, data sourcing, and customer enablement.
- Apply AI technologies and modern engineering practices to identify opportunities for process transformation.
- Collaborate across technical and business teams to solve complex problems and create scalable solutions.
- Drive continuous improvement by identifying bottlenecks and reducing friction in end-to-end experiences.
Skills
Tools
Job description
Chainlink Labs is seeking a Software Engineer in Data Growth to build scalable automation and self-service experiences that streamline customer onboarding and product adoption. You will apply AI-enabled solutions and systems thinking to improve efficiency across growth-related processes.
The role emphasizes collaboration across technical and business teams to solve complex problems and deliver measurable improvements in onboarding cycle times and data provisioning.
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