5 дней назад
AI Success Engineer
90 000 - 140 000GBP
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
AI Success Engineer (AI/Knowledge Graphs): Building and deploying AI-powered enterprise solutions that integrate structured and unstructured data into knowledge graphs, with an accent on customer discovery, technical architecture, and LLM-based workflows. Focus on translating ambiguous business problems into deployable systems, leading implementation with customer stakeholders, and shaping repeatable solution patterns.
Location: In office in London or Berlin
Salary: £90,000–£140,000 base/bonus, plus meaningful equity
Company
builds open-source infrastructure and knowledge graph technology for integrating information, simulating processes, and supporting AI-driven decision-making.
What you will do
- Partner with customers to understand workflows, data, and operational challenges.
- Design and build AI-powered solutions for enterprise use cases.
- Translate ambiguous business problems into structured technical plans and deployable systems.
- Work across knowledge graphs, structured and unstructured data, LLM-based workflows, and automation.
- Lead technical discovery, solution design, implementation, and rollout with customer stakeholders.
- Collaborate with product, engineering, and research to shape the platform and define repeatable delivery patterns.
Requirements
- Strong technical ability with experience shipping software or building AI systems in production.
- Background in AI/ML engineering, data engineering, applied AI, or product engineering.
- Ability to work directly with customers and own complex problem-solving end to end.
- Clear, structured communication and strong judgment in ambiguous, fast-moving environments.
- High agency, execution focus, and genuine interest in helping customers achieve measurable results.
Culture & Benefits
- Work on first-principles AI research connected to real-world applications.
- Join a rapidly growing European AI lab with broad scope and influence.
- Open-source, long-term-oriented working environment.
- Quarterly in-person whole-team retreats.
- Generous learning and technology budgets, competitive compensation, tax-advantaged options, and meaningful equity.
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