7 часов назад
AI Tech Lead (GraphAware Hume)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
AI Tech Lead (GraphAware Hume) (AI/LLM/Graph AI): Designing and building the AI layer for Hume Maestro, Neo4j’s connected data analytics platform, with an accent on AI architecture, graph-based AI, and production-ready engineering. Focus on implementing scalable AI components, model evaluation, deployment pipelines, and integration with product, science, frontend, and platform teams.
Location: Remote within EMEA; candidates are targeted in the UK, Czechia, or Italy
Company
develops a graph intelligence platform with enterprise knowledge graphs and graph capabilities for AI systems and connected data applications.
What you will do
- Design the foundations and technical roadmap of the AI layer for Hume, with an initial focus on Hume Maestro.
- Contribute hands-on to the codebase and set standards for performance, scalability, and technical quality.
- Translate product vision and research direction into production-ready technical decisions.
- Work with Product Managers and the Chief Scientist within a shared decision-making framework.
- Integrate AI capabilities with frontend and platform components across the Hume product.
- Establish AI/ML engineering practices covering model evaluation, deployment pipelines, and maintainable code structures.
Requirements
- Senior or Lead Engineer experience with deep expertise in artificial intelligence and machine learning.
- Strong experience designing and deploying AI architectures, particularly with LLMs, graph-based AI, or complex data processing layers.
- Ability to connect high-level research and product vision with production-ready engineering.
- Experience collaborating with Product and Science stakeholders while balancing technical debt, innovation, and delivery speed.
- Communication skills for coordinating complex technical projects and a desire to build and mentor an AI engineering team.
Nice to have
- Experience in B2B SaaS or high-growth deep-tech environments.
Culture & Benefits
- Collaborative, inclusive, and intellectually honest working environment.
- Shared decision-making and autonomy to contribute to projects.
- Opportunity to shape a core AI capability from the ground up.
- Potential to transition from an individual contributor or lead role into building and mentoring an AI engineering team.
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