About the Role
Lead the design and implementation of AI-powered solutions while mentoring engineers and shaping technical direction across projects.
Responsibilities
- Lead the architecture and development of AI-driven software systems
- Mentor and support engineers in best practices for machine learning and data modeling
- Collaborate with product and research teams to define technical roadmaps
- Translate business requirements into scalable technical solutions
- Oversee code quality, testing, and system reliability
- Drive innovation in natural language processing and knowledge representation
- Guide integration of AI components with enterprise platforms
- Participate in client technical discussions and solution design
- Ensure alignment with data privacy and security standards
- Lead technical decision-making across development cycles
- Evaluate and introduce new tools and frameworks for AI development
- Support deployment and monitoring of production AI systems
- Foster knowledge sharing within the engineering group
- Contribute to technical documentation and system design specs
- Manage technical risks in project execution
- Work closely with data scientists to operationalize models
- Promote efficient use of graph-based data structures in AI workflows
- Lead proof-of-concept initiatives for new AI capabilities
- Ensure solutions are maintainable and extensible
- Coordinate with DevOps for CI/CD pipelines
- Advocate for user-centric design in AI features
- Troubleshoot complex system behaviors involving AI components
- Balance innovation with delivery timelines
- Stay current with advancements in AI and semantic technologies
- Support technical onboarding for new team members
Nice to Have
- Master’s degree in Computer Science or related field
- Experience with large-scale data processing frameworks
- Contributions to open-source AI or graph projects
- Publications or presentations in AI or data science venues
- Hands-on work with transformer-based models
- Experience in regulated industries such as finance or healthcare
- Knowledge of ontology engineering
- Familiarity with MLOps practices
- Experience leading distributed teams
- Background in formal methods or logic programming
Compensation
Competitive salary with performance-based incentives
Work Arrangement
Hybrid remote with office options in London and Belgium
Team
Collaborative engineering team focused on AI and knowledge graph technologies
Technology Stack
Java, Python, Neo4j, AWS, Docker, Kubernetes, Git, TensorFlow, PyTorch, LangChain, FastAPI
Professional Development
Access to training courses, conference attendance, and dedicated R&D time
Client Engagement
Opportunities to work directly with enterprise clients on AI strategy and implementation
Innovation Time
Regular hackathons and internal project incubation periods
Work Culture
Emphasis on technical excellence, transparency, and mutual respect
Available for qualified candidates
