Blockchain Engineers

Maintain and support distributed and decentralized blockchain-based networks or block-chain applications such as cryptocurrency exchange, payment processing, document sharing, and digital voting. Design and deploy secure block-chain design patterns and solutions over geographically distributed networks using advanced technologies. May assist with infrastructure setup and testing for application transparency and security.

The automation risk for the occupation "Blockchain Engineers" has been assessed at 51.5%, reflecting a moderate likelihood that core aspects of the job could be automated in the foreseeable future. The role involves significant technical tasks that can benefit both from automation as well as human oversight. The top three most automatable tasks in this position include assessing blockchain threats such as untested code and unprotected keys, automating the deployment of software updates over geographically distributed network nodes, and designing and deploying blockchain design patterns to make transactions secure, transparent, and immutable. These tasks rely heavily on rule-based processes, standardization, and repeatable workflows, making them attractive candidates for automation technologies such as advanced scripting, machine learning algorithms, and deployment orchestration tools. However, the occupation also consists of highly complex and dynamic responsibilities that currently demonstrate resistance to full automation. The top three most resistant tasks for blockchain engineers include updating client and server applications responsible for integration and business logic, testing the security and performance of blockchain infrastructures, and running infrastructure tests to examine the behavior of large peer-to-peer networks. These responsibilities demand deep context-specific understanding, on-the-fly problem-solving, and a nuanced grasp of business requirements, all areas where human expertise still significantly outperforms automated systems. Since blockchains actively evolve with new threats and integration scenarios, continuous hands-on analysis and adaptive decision-making are required on a case-by-case basis. Key bottleneck skills that influence the automation risk in this field include advanced software engineering (Expert level), cryptographic protocol analysis (Advanced level), infrastructure and network troubleshooting (Advanced level), and business logic design (Advanced level). These skills introduce complexity that challenges current automation capabilities: expert software engineers must architect systems robust enough to withstand both novel and routine blockchain challenges, while cryptographic skills are essential to ensure the integrity and security of decentralized applications. Meanwhile, network and infrastructure troubleshooting calls for rapid diagnosis and resolution that adapts to intricate, real-world scenarios, and business logic design requires aligning technical solutions with unique organizational needs. Altogether, these bottleneck skills ensure that while automation can streamline or augment parts of the blockchain engineer’s role, substantial components remain dependent on specialized human expertise.