About the Role
The candidate will lead the development and optimization of knowledge management systems, working closely with cross-functional teams to deliver robust, maintainable software solutions.
Responsibilities
- Design and implement scalable components for knowledge management platforms
- Collaborate with product teams to define system requirements
- Improve system reliability and performance through iterative development
- Conduct code reviews and ensure adherence to engineering standards
- Diagnose and resolve complex technical issues in production environments
- Support integration of new features with existing architecture
- Document technical designs and system workflows
- Mentor junior engineers in best practices and coding standards
- Evaluate emerging technologies for potential adoption
- Participate in sprint planning and agile development cycles
- Ensure compliance with data governance and security policies
- Optimize database queries and data access patterns
- Develop automated testing frameworks for regression coverage
- Coordinate with operations for deployment and monitoring
- Refactor legacy code to improve maintainability
- Implement monitoring and alerting for critical services
- Contribute to API design and versioning strategies
- Support incident response and root cause analysis
- Facilitate knowledge transfer across engineering teams
- Drive improvements in build and deployment pipelines
- Ensure system designs align with long-term technical roadmap
- Collaborate on user authentication and authorization mechanisms
- Integrate third-party tools and services securely
- Promote code quality through static analysis and linting
- Assist in capacity planning for infrastructure needs
Nice to Have
- Master's degree in computer science or related field
- Experience with knowledge graph technologies
- Familiarity with natural language processing concepts
- Background in semantic data modeling
- Experience with graph databases such as Neo4j
- Knowledge of machine learning pipelines
- Contributions to open-source projects
- Experience in educational technology domains
- Understanding of metadata standards
- Exposure to large-scale data ingestion systems
- Experience with search engine technologies
- Familiarity with ontology design
- Background in information retrieval systems
- Knowledge of data provenance and lineage tracking
- Experience with collaborative editing systems
Compensation
Competitive salary with performance-based incentives
Work Arrangement
Hybrid work model with flexible scheduling
Team
Collaborative engineering unit focused on knowledge management systems
Technology Stack
- Primary languages include Java and Kotlin
- Infrastructure leverages Kubernetes and Docker
- Data stores include PostgreSQL and Neo4j
- Cloud environment hosted on AWS
- CI/CD powered by Jenkins and GitHub Actions
Growth Opportunities
- Access to technical leadership pathways
- Opportunities to lead architecture initiatives
- Support for conference participation and speaking engagements
- Internal tech talks and knowledge-sharing forums
- Budget for courses and certifications
Available for qualified candidates