Pubblicato il 17 giugno
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Experteer Overview In this role you will design and govern production-grade GenAI and retrieval-augmented systems for internal use across global teams. You will own end-to-end GenAI architecture, establish RAG strategies, and align with GDPR, data residency, and enterprise IT standards. You'll lead engineering efforts, integrate AI into data platforms, and mentor others while focusing on reliability, security, and transparency. This opportunity puts you at the core of scalable AI enablement within an IoT-focused company.
Retribuzione / Benefits Own end-to-end GenAI architecture for internal use cases
Define RAG reference architectures and embedding/retrieval strategies
Evaluate build vs. buy with clear trade-offs
Design multi-source RAG pipelines (structured + unstructured)
Implement advanced retrieval patterns (hybrid search, reranking, context compression)
Address enterprise failure modes (stale knowledge, conflicting sources, access control)
Define KPIs (precision/recall, grounded ness, hallucination rate) and AI Act-aligned transparency artifacts
Build production services (APIs, batch jobs, internal tools)
Integrate GenAI into data platforms and analytics workflows
Ensure logging, observability, cost monitoring, and feedback loops
Act as technical authority for GenAI and mentor engineers/data scientists
Educate stakeholders on GenAI capabilities and limitations
Responsabilità Strong Python
CI/CD
Enterprise SDLC
Hands-on GenAI & RAG expertise beyond demos
Embeddings, retrieval tuning
Vector databases
SQL and object storage
Containerized deployments
GDPR, data residency, RBAC
Collaboration with Legal/DPO
5–8+ years in software/ML engineering
2+ years in GenAI/NLP systems
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