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Nexthink

Discover what your employees need, see what they experience, know how they feel. Deliver IT that delights.

We are seeking a Senior Engineer with experience building and operating AI-powered software systems. You will join one of the AI teams and be responsible for prototyping, maturing, and shipping AI features to a production-ready level. You will also integrate external AI services (e. g., LLM providers) into Nexthink's cloud platform.

You are a pragmatic, results-driven engineer who understands modern AI stacks but thinks in terms of software reliability, performance, and user impact. You focus on creating scalable, observable solutions that solve real-world problems for our customers. Because the role is cross-functional, the ability to communicate complex concepts in simple ways is essential. You will collaborate with product, design, front-end, and infrastructure teams to bring delightful AI features to life.

Requirements:

  • BSc/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 developer working on building microservices, strong experience in Java, Kafka, Event driven Architecture.
  • Minimum of 1-2 years of considerable experience in writing production-ready code for delivering AI applications.
  • Experience in integrating with LLMs (e. g. Prompting, Evaluation, Observability).
  • Demonstrated success delivering AI-powered features that serve real users at scale (e. g., retrieval-augmented search, Generative AI assistants, predictive analytics).
  • Fluency in Python or at least one strongly-typed language (TypeScript or Java), with clean code and testing discipline.
  • Solid grasp of cloud-native architectures (AWS or comparable), containerisation (Docker), and orchestration (Kubernetes / ECS).
  • Hands-on experience with MLOps: reproducible pipelines, automated evaluations, feature stores, CI/CD for models or prompt/embedding configs.
  • Strong data intuition: ability to inspect raw logs, design metrics, and quickly identify quality regressions.
  • Product mindset and empathy for end-users; able to translate fuzzy product requirements into incremental engineering plans.
  • Excellent communication and collaboration skills in English (spoken and written).

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