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VP of Technology
Исключительная возможность для технического лидера возглавить перспективный AI-стартап с реальной выручкой и именитыми клиентами. Высокий потенциал карьерного роста до CTO и работа с передовыми технологиями.
Сложность вакансии
Роль требует редкого сочетания глубоких знаний в ML-инфраструктуре, системах с низкой задержкой и управленческого опыта уровня VP в стартапе. Высокая планка ответственности за архитектуру и рост команды до 20 человек делает позицию крайне сложной.
Анализ зарплаты
Для позиции VP of Technology в Берлине в сфере AI, предлагаемый рыночный диапазон составляет 140,000–180,000 евро в год плюс опционы. Учитывая стадию компании и сложность стека, компенсация должна находиться в верхней границе рынка.
Сопроводительное письмо
I am writing to express my strong interest in the VP of Technology position at Journee. With over a decade of experience in engineering leadership and a deep background in building scalable distributed systems, I am particularly drawn to Journee’s mission of creating low-latency conversational AI. My experience in optimizing ML inference and managing high-concurrency enterprise platforms aligns perfectly with your current goals for the Ojin platform and your work with clients like BMW and H&M.
Throughout my career, I have maintained a 'builder' mentality, balancing high-level architectural strategy with hands-on technical execution. I have successfully led engineering teams through rapid growth phases, focusing on performance optimization and developer experience. I am excited by the prospect of leading your talented team of engineers and contributing to the evolution of your real-time AI infrastructure as you scale toward a CTO-level leadership structure.
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Описание вакансии
VP of Technology
Who We Are
We’re Journee — The Human AI company.
We build real-time conversational AI agents for enterprise brands, powered by our own low-latency streaming and AI infrastructure. Our proprietary low-latency streaming and GPU orchestration infrastructure powers interactive AI experiences used by companies like BMW, H&M, Siemens, WWF, and Condé Nast.
We recently launched Ojin, our developer platform for building and scaling real-time AI agents. It provides the APIs, inference infrastructure, and orchestration layer needed to run conversational AI systems in production.
The RoleThis is a hands-on technical leadership role.
You will lead a team of up to 10 engineers (ML, backend, frontend, infra), while remaining deeply involved in architecture, performance optimization, and product direction. We’re looking for a high energy builder — someone ambitious, technically sharp, and excited to grow into a CTO level leader over time.
This is for someone who wants to build something meaningful and take ownership of a real system — not just manage one.
What You’ll Own
Architecture & Technical Direction
- Own overall system architecture across:
- Conversational AI systems (LLMs, orchestration, real-time inference)
- Voice + avatar pipelines (latency-sensitive systems)
- Developer platform (APIs, SDKs, tooling, observability)
- Drive our cloud infrastructure strategy (AWS/GCP/Azure)
Ensure scalability, reliability, and enterprise-grade security
Performance & ML Systems
- Optimize real-time AI inference (latency, throughput, cost)
- Improve orchestration of models (LLMs, TTS/STT, and related components)
- Design systems that handle high concurrency at enterprise scale
- Balance latency, cost, and product quality across deployments
Developer Platform
- Lead API architecture and SDK strategy
- Improve developer onboarding and self-serve capabilities
- Build scalable abstractions for agent creation and deployment
- Strengthen observability, debugging, and developer tooling across the platform
Team & Culture
- Lead and mentor a team of up to 10 engineers
- Attract and hire strong technical talent
- Set a culture of ownership, velocity, and accountability
- Keep planning and delivery lightweight, focused, and effective
Hands-On Contribution
- Review architecture and critical code paths
- Prototype and unblock high impact work
- Step into performance or production challenges when needed
What We’re Looking For
- 8-12+ years in engineering, including leadership experience
- Experience leading engineering teams (5+ engineers)
- Strong cloud architecture background (AWS/GCP/Azure)
- Deep understanding of distributed systems and scalable backend architecture, including APIs and platform design
- Experience running ML systems in production
- Strong full-stack understanding (backend + frontend)
- Experience working directly with founders
Highly Valuable Experience:
- ML inference performance optimization
- Real-time/low-latency systems
- Building developer platforms or APIs at scale
- Startup or scale-up background
Profile Fit
- Builder mentality - not just a manager
- High ownership and strong execution energy
- Comfortable with ambiguity
- Product minded, not purely infrastructure driven
- Willing to lead and code
What Success Looks Like (12 Months)
- Reduced latency and optimized inference costs
- Developer onboarding simplified and platform adoption increased
- Enterprise-grade reliability and scalability across customer deployments
- Clear technical roadmap aligned with product strategy
- A strong culture of ownership and execution
- Team grown to 15-20 high quality engineers
Why Join
- Real product-market validation
- Revenue-generating AI platform
- Real traction in enterprise conversational AI
- Direct impact on architecture and culture
- Opportunity to grow into CTO
Journee is committed to creating a diverse and inclusive workplace where everyone is treated with dignity, respect, and fairness. We value diversity in all its forms, including but not limited to race, ethnicity, gender, sexual orientation, age, religion, national origin, disability, and veteran status. We believe that a diverse and inclusive workplace leads to better business outcomes, stronger relationships with our customers and partners, and a more fulfilling work experience for our employees.
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Навыки
- Machine Learning
- Distributed Systems Architecture
- AWS
- Google Cloud Platform
- Azure
- API Design
- SDK Development
- Scalability
- Infrastructure
- Backend Development
- Frontend Development
- MLOps
Возможные вопросы на собеседовании
Позиция требует оптимизации инференса ИИ в реальном времени.
Какие стратегии вы использовали для снижения задержки (latency) в распределенных ML-системах при сохранении высокой пропускной способности?
Компания развивает платформу Ojin для разработчиков.
Как вы подходите к проектированию API и SDK, чтобы обеспечить бесшовный опыт адаптации (onboarding) для сторонних разработчиков?
Роль предполагает рост команды с 10 до 20 человек.
Опишите ваш процесс найма и удержания топовых инженеров в условиях жесткой конкуренции на рынке AI/ML.
Journee работает с крупными брендами (BMW, H&M).
Как вы обеспечиваете баланс между скоростью разработки стартапа и требованиями корпоративной безопасности и надежности (enterprise-grade)?
Это роль 'играющего тренера'.
Как вы распределяете свое время между написанием/ревью кода и стратегическим планированием архитектуры?
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1000+ офферов получено
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