- Страна
- Дания
Откликайтесь
на вакансии с ИИ

Senior Applied AI Engineer
Отличная вакансия в быстрорастущем MedTech стартапе с современным стеком (LLM, Agents, Go, Kubernetes). Высокий балл за социальную значимость проекта и работу с передовыми технологиями ИИ.
Сложность вакансии
Роль требует глубоких знаний в области LLM, RAG и агентных фреймворков, а также умения писать промышленный код на Python и Go. Высокая сложность обусловлена необходимостью работы с медицинскими данными и строгими требованиями к надежности систем.
Анализ зарплаты
Зарплата в объявлении не указана, но для позиции Senior AI Engineer в Копенгагене рыночный диапазон составляет 700,000–950,000 DKK в год. Предложение Corti, вероятно, находится в этих пределах или выше, учитывая дефицитность навыков в области Agentic AI.
Сопроводительное письмо
I am writing to express my strong interest in the Senior Applied AI Engineer position at Corti. With a deep background in building production-grade LLM systems and a passion for healthcare innovation, I am drawn to Corti’s mission of making medical expertise accessible through agentic frameworks and robust AI infrastructure.
In my previous experience, I have successfully deployed RAG architectures and optimized low-latency inference services using NVIDIA Triton and FastAPI. I have a proven track record of moving beyond model experimentation to building scalable, reliable product features. My expertise in designing evaluation frameworks for agentic workflows aligns perfectly with your goal of creating dependable, medical-grade AI.
I am particularly excited about the opportunity to work at the intersection of AI and product engineering in your Copenhagen office. I am confident that my technical skills in Python and Go, combined with my commitment to precision and safety in AI, will allow me to make an immediate impact on your team and the millions of patients Corti serves.
Составьте идеальное письмо к вакансии с ИИ-агентом

Откликнитесь в corti уже сейчас
Присоединяйтесь к Corti, чтобы создавать ИИ-агентов, которые спасают жизни и меняют будущее мирового здравоохранения.
Описание вакансии
Overview
We are on a mission to ensure everyone has access to medical expertise, no matter where they are.
Half the world still lacks access to quality healthcare. Even in advanced systems, outcomes are uneven, and clinicians are overwhelmed. Medical knowledge grows faster than human capacity can keep up.
Corti is building the infrastructure to close that gap. Our AI platform expands access to medical expertise, reducing errors, restoring time to clinicians, and making care more affordable, accessible, and human again.
There is no quality healthcare without a quality dialogue, and no reliable AI without a strong foundation. Help us build both.
Why Corti?
Corti is building the intelligence layer for global healthcare. We give every developer, product team, and healthcare innovator access to medical-grade AI, so the world can deliver care that is faster, safer, and more human.
Built entirely for healthcare and adjacent industries, Corti’s models are trained on real-world data and optimized for precision, safety, and regulatory trust.
Through modular APIs, teams can embed medical speech recognition, summarization, reasoning, and much more directly into healthcare products without reinventing the foundation.
We power the builders who are redefining how healthcare works, from startups creating new patient experiences to enterprises modernizing the systems that care depends on.
If you believe that AI purpose-built for medicine will define the next century of healthcare, you belong at Corti.
The Role
As a Senior AI Engineer focused on agentic framework, you will focus on building LLM-powered systems and agentic workflows that power core product capabilities at Corti. You will work on building strong validation practices, and deploying low-latency inference services that are dependable in real-world conditions.
You will work at the intersection of AI, product, and engineering, designing and implementing systems that leverage large language models, retrieval architectures, and context-aware agents to solve complex real-world problems.
This is a hands-on engineering role for someone who enjoys building production systems—not just experimenting with models.
What you’ll be doing
- Design and build LLM-powered product features used in production.
- Develop agentic workflows and frameworks that coordinate multiple AI components.
- Implement RAG (Retrieval-Augmented Generation) architectures using embeddings and vector search.
- Build systems for prompting, context engineering, and tool usage.
- Develop evaluation frameworks to measure LLM and agent performance.
- Work closely with product and platform teams to turn AI capabilities into reliable, scalable product features.
- Continuously improve system reliability, latency, and cost efficiency of AI pipelines.
Technologies you may work with
- Apache Kafa
- NVIDIA Triton Inference Server
- FastAPI for ML APIs and services
- Go for backend services
- Kubernetes for deployment and operations
- Common MLOps tooling for experiment tracking, model versioning, and monitoring
What you bring
- Strong programming skills in Python and the ability to contribute to production-grade codebases.
- Hands-on experience in LLMs, including at least some of the following:
+ Training, finetuning, or post-training transformer-based models.
+ Building or operating LLM inference services in production, including performance work.
+ Experience with embeddings, vector databases, and semantic search.
+ Practical experience implementing RAG architectures.
+ Designing robust evaluations for agent workflows and generative systems, including metrics, error analysis, and human evaluation methods.
- Experience building production-graded ML systems that can be deployed and operated, including pipelines, CI and CD practices, and monitoring.
- Strong product mindset with the ability to translate ideas into working systems
- Clear communication and collaboration skills across research, engineering, and product.
- A Master’s degree in computer science, engineering, mathematics, statistics, physics, or a related field, or equivalent professional experience.
- Nice to have: Experience with healthcare data, clinical NLP, privacy and safety considerations. Experience with Go.
Life at Corti
- You will be reporting to the VP of Product
- The position is full-time and starts as soon as possible
- Hybrid working environment in our Copenhagen Office
- Equipment provided by Corti
Ready to dive into the world of Corti? Hit that 'Apply' button, and let's start working together on reshaping the dialogue in healthcare, making a real difference for millions of patient outcomes around the world.
🤝 Bringing in top talent from all backgrounds is crucial in our pursuit to improve the world of healthcare. We encourage applications from all people and do not discriminate based on race, religion, national origin, gender, sexual orientation, age, and/or disability status.
At Corti, experience comes in many forms, and we’re passionate about creating teams with a multitude of perspectives! If you believe your experience is close to what we’re looking for but not an exact match, we still hope you’ll consider applying!
Создайте идеальное резюме с помощью ИИ-агента

Навыки
- Python
- LLM
- Kubernetes
- MLOps
- RAG
- NLP
- Apache Kafka
- Go
- FastAPI
- Vector Databases
- Semantic Search
- NVIDIA Triton Inference Server
Возможные вопросы на собеседовании
Проверка практического опыта работы с агентными системами и понимания их жизненного цикла.
Расскажите о самом сложном агентном ворклоу (agentic workflow), который вы проектировали для продакшена. С какими проблемами зацикливания или галлюцинаций вы столкнулись?
Оценка навыков оптимизации производительности, критически важных для медицинских сервисов реального времени.
Как бы вы оптимизировали задержку (latency) для системы RAG, использующей тяжелые эмбеддинги и большой контекст в LLM?
Проверка умения оценивать качество генеративных систем, что является ключевым требованием вакансии.
Какие метрики и методы валидации вы считаете наиболее эффективными для оценки точности медицинских суммаризаций?
Оценка опыта работы с инфраструктурой, упомянутой в стеке (Triton, Kubernetes).
Опишите ваш опыт развертывания моделей через NVIDIA Triton Inference Server. Какие преимущества это дает по сравнению со стандартным FastAPI эндпоинтом?
Проверка продуктового мышления и этического подхода к ИИ в медицине.
Как вы подходите к обеспечению безопасности и минимизации рисков при использовании LLM в продуктах, напрямую влияющих на принятие клинических решений?
Похожие вакансии
AI Engineer (CV & Navigation)
Senior / Lead LLM Engineer
Middle, Middle+, Senior GenAI/LLM Разработчик
Senior Python AI Developer
GenAI/LLM Разработчик
Middle / Senior GenAI Engineer (CV)
1000+ офферов получено
Устали искать работу? Мы найдём её за вас
Quick Offer улучшит ваше резюме, подберёт лучшие вакансии и откликнется за вас. Результат — в 3 раза больше приглашений на собеседования и никакой рутины!
- Страна
- Дания