About the Role
Responsibilities
Build and maintain the data infrastructure to enable multi agent cloud to device processes.
Key Activities
Data Engineering (knowledge graph pipelines, MongoDB schemas, data processing)
Portal Development (React applications, partner interfaces, requirement capture tools)
System Integration (API consumption, ML scoring integration, cloud-to-device data flow)
Tasks
Read initiatives, review wireframes, process diagrams, and data requirements in order to draft solution options during the architecture review including level of effort for implementation.
Collaborate with the Platform Architect on those options to ensure they follow best practices.
Translate the options into high code quality that adheres to Swift and Honestum best practices. Write tests to ensure code quality and prevent regressions.
Participate in grooming calls to get clarification on the business requirements and execute sprint demos to share progress. Work with business planning on the talk track of these demos.
Debug issues found during user acceptance testing (UAT). Including monitoring and debug performance issues (load times, memory, crash rates, etc). Escalate to Platform Architect when blocked.
Document feature during technical handover to ensure the platform is maintainable.
Build and maintain knowledge graph construction pipelines (Text → Node conversion) for theological content processing.
Develop React-based partner portals for domain expert interaction and content management.
Design and optimize MongoDB schemas and data pipelines for efficient storage and retrieval.
Integrate ML scoring systems from ML Engineer into portal interfaces for quality tracking.
Consume APIs from ML Engineer for agent services and ensure efficient data flow between systems.
Work with Account Manager to implement template-based requirement capture tools in partner portals.
Skills Set (Must Have)
5+ years full-stack development with React, Node.js, and MongoDB at scale
Track record designing and building data processing pipelines and ETL systems for production environments
Experience architecting user-facing portals with complex data management and API integrations
Strong software engineering practices: testing, performance optimization, and technical documentation
Skills Set (Nice to Have)
Experience with knowledge graph technologies or graph database concepts
Familiarity with ML model integration and scoring system APIs
Background working with domain experts or non-technical stakeholders
Experience with cloud platforms (AWS, Azure, GCP) for data infrastructure