Full Stack Engineer – AI Systems
New
J
JobgetherAI productivity software
Based in NetherlandsFull-Time
Salary not disclosed
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Job Details
- Required Skills
- DockerNode.jsPythonSQLKubernetesNext.jsNosqlDistributed Systems
Requirements
- Strong professional experience building full-stack applications with modern technologies and frameworks, particularly Next.js, Python, and Node.js.
- Hands-on experience developing AI-powered applications, implementing RAG systems, or integrating LLM APIs.
- Experience with LLM providers such as OpenAI or Anthropic, or open-source model ecosystems.
- Understanding of application architecture, API design, and distributed systems concepts.
- Knowledge of database technologies, including SQL and NoSQL.
- Experience with containerization, deployment pipelines, and cloud orchestration technologies such as Docker and Kubernetes.
- Ability to design robust user experiences that account for latency, non-deterministic model outputs, graceful degradation, and unexpected failures.
- Proven ability to take features from concept through development, deployment, and ongoing optimization.
- User-focused approach to reliability, usability, responsiveness, and the practical value of AI features.
- Ability to work effectively with cross-functional engineering and machine learning teams.
- Must be based in the Netherlands and able to collaborate effectively within a fully remote team.
Responsibilities
- Develop and maintain full-stack features across frontend interfaces, backend services, and AI integrations.
- Create agentic workflows that plan, execute tasks, use tools, handle failures, and recover across sessions.
- Integrate LLMs, memory architectures, RAG systems, and external APIs.
- Build real-time interfaces that support streaming responses, partial results, and low-latency interactions.
- Improve observability, monitoring, error handling, fallback mechanisms, and recovery strategies.
- Analyze user feedback, behavioral signals, and telemetry to evaluate models and guide product improvements.
- Collaborate with machine learning and backend teams on scalable architectures, API structures, and reusable integration patterns.
- Own technical implementation and deliver features from concept through production and ongoing optimization.
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