Senior AI Software Engineer ( SDE V)

We are looking for a Senior Engineer with experience building and operating AI-powered software systems to join one of our AI teams.

In this role, you will be responsible for prototyping, maturing, and shipping AI features to a production-ready level.

You will also integrate external AI services, such as large language model (LLM) providers, into our cloud platform.

You are a pragmatic, results-driven engineer who understands modern AI stacks but prioritizes software reliability, performance, and user impact.

You'll focus on creating scalable, observable solutions that solve real-world problems for our customers.

This is a cross-functional role, so the ability to communicate complex concepts simply is essential.

You'll collaborate with product, design, front-end, and infrastructure teams to bring delightful AI features to life.

Qualifications :

- BSc or MSc in Computer Science, Software Engineering, or a related field.

- 8+ years of professional software engineering experience, including shipping and operating cloud services in production.

- Strong backend development experience building microservices, with a focus on Java, Kafka, and event-driven architecture.

- Minimum of 1-2 years of experience writing production-ready code for AI applications.

- Experience integrating with LLMs, including prompting, evaluation, and observability.

- Demonstrated success in delivering AI-powered features that serve real users at scale (e., retrieval-augmented search, generative AI assistants, predictive analytics).

- Fluency in Python or at least one strongly-typed language (TypeScript or Java), with a strong discipline for clean code and testing.

- Solid grasp of cloud-native architectures (AWS or a comparable provider), containerization (Docker), and orchestration (Kubernetes/ECS).

- Hands-on experience with MLOps, including reproducible pipelines, automated evaluations, feature stores, and CI/CD for models or prompt/embedding configurations.

- Strong data intuition and the ability to inspect raw logs, design metrics, and quickly identify quality regressions.

- A product mindset and empathy for end-users, with the ability to translate fuzzy product requirements into incremental engineering plans.

- Excellent communication and collaboration skills in English (spoken and written).