[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-ai-engineer-llm-and-rag-systems":3,"similar-ai-engineer-llm-and-rag-systems":32},{"id":4,"slug":5,"title":6,"skills":7,"budget":16,"duration":17,"location":18,"onsitePercent":19,"contractType":20,"foundAt":21,"category":22,"description":26,"rawText":27,"webTitle":28,"webText":29,"language":30,"projectId":16,"sourceUrl":31},10341,"ai-engineer-llm-and-rag-systems","AI Engineer - LLM and RAG Systems",[8,9,10,11,12,13,14,15],"Python","LLMs","RAG","embeddings","prompt engineering","AWS","vector databases","microservices",null,"3 Monate (Verlängerung erwartet, ~1 Jahr Gesamtlaufzeit)","Utrecht",50,"contracting","2026-06-03T06:04:26+00:00",{"id":23,"slug":24,"label":25},3,"ai_ml","AI & Machine Learning","3-month contract (extension expected) for hands-on AI Engineer to build production-grade LLM and RAG systems for large-scale document processing. Applied AI engineering role building real features used daily, not research.","\u003Cp>\u003Cstrong>3‑month contract (extension expected | total contribution ~1 year)\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Start: ASAP | Location: Utrecht \u002F Remote hybrid\u003C\u002Fstrong>\u003C\u002Fp>\n\u003C\u002Fp>\n\u003Cp>We’re looking for a hands-on \u003Cstrong>AI Engineer\u003C\u002Fstrong> to strengthen an AI engineering team building production-grade \u003Cstrong>LLM and RAG systems\u003C\u002Fstrong> for large‑scale document processing. This is not a research role – it’s \u003Cstrong>applied AI engineering\u003C\u002Fstrong>, building real features used daily.\u003C\u002Fp>\n\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>What you’ll do\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cul>\n\u003Cli>Build and improve LLM\u002FRAG pipelines for processing large document sets\u003C\u002Fli>\n\u003Cli>Develop Python microservices powering GenAI features\u003C\u002Fli>\n\u003Cli>Work with embeddings, vector databases, and retrieval logic\u003C\u002Fli>\n\u003Cli>Build data ingestion & document processing workflows\u003C\u002Fli>\n\u003Cli>Deploy and operate solutions in an AWS environment\u003C\u002Fli>\n\u003Cli>Collaborate with a small group of AI engineers & developers\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Ch3>\u003Cstrong>What you bring\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cul>\n\u003Cli>Strong \u003Cstrong>Python\u003C\u002Fstrong> engineering fundamentals\u003C\u002Fli>\n\u003Cli>Hands-on experience with \u003Cstrong>LLMs\u003C\u002Fstrong>, embeddings, RAG, and prompt engineering\u003C\u002Fli>\n\u003Cli>Experience deploying AI solutions, preferably in \u003Cstrong>AWS\u003C\u002Fstrong>\u003C\u002Fli>\n\u003Cli>Bonus: web crawling, Java\u002Fbackend knowledge\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Ch3>\u003Cstrong>Why this role\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cul>\n\u003Cli>3 months to start, with a high likelihood of \u003Cstrong>multi‑extension\u003C\u002Fstrong> (1-year scope)\u003C\u002Fli>\n\u003Cli>Key contribution to a rapidly scaling GenAI platform\u003C\u002Fli>\n\u003Cli>Freedom to experiment and move fast with modern AI tooling\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>Darwin Recruitment is acting as an Employment Business in relation to this vacancy.\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fcounter.adcourier.com\u002FTWFudWVsLlJlYm9sby4zNDE0Mi4xMjc4NEBkYXJ3aW4uYXBsaXRyYWsuY29t.gif\">\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"color: #ffffff\">Manuel Rebolo\u003C\u002Fspan>\u003C\u002Fp>\nAnsprechpartner: Manuel Rebolo\nE-Mail: Manuel.Rebolo@darwinrecruitment.com\nTelefon: +31 (0)20 305 0084","AI Engineer - LLM\u002FRAG Systems Development","We are seeking a hands-on AI Engineer to join our AI engineering team focused on building production-grade LLM and RAG systems for large-scale document processing. This is an applied AI engineering position, not a research role, where you will build real features used in daily operations.\n\nIn this role, you will build and improve LLM\u002FRAG pipelines for processing extensive document sets and develop Python microservices that power GenAI features. You will work extensively with embeddings, vector databases, and retrieval logic while building data ingestion and document processing workflows. The position involves deploying and operating solutions in an AWS environment and collaborating with a small team of AI engineers and developers.\n\nWe are looking for candidates with strong Python engineering fundamentals and hands-on experience with LLMs, embeddings, RAG, and prompt engineering. Experience deploying AI solutions, preferably in AWS, is essential. Additional experience with web crawling and Java\u002Fbackend knowledge would be advantageous.\n\nThis is a 3-month contract position with high likelihood of extension, potentially contributing for approximately one year total. You will make key contributions to a rapidly scaling GenAI platform with the freedom to experiment and move fast using modern AI tooling. The role offers a hybrid working arrangement combining remote work with office presence.\n\nThis opportunity is perfect for an AI engineer who wants to work on cutting-edge technology in a fast-paced environment, building solutions that have immediate real-world impact. Join our team and help shape the future of AI-powered document processing systems.","en","https:\u002F\u002Fwww.darwinrecruitment.com\u002Fjob\u002F8341427831457-ml-engineer-utrecht-utrecht\u002F",{"items":33},[34,50,65,76,91,106,125,148,169,180,190,208,226,244,265],{"id":35,"slug":36,"title":37,"skills":38,"budget":16,"duration":16,"location":16,"onsitePercent":16,"contractType":20,"foundAt":48,"category":49},10464,"computer-vision-engineer-for-robotics-perception-stack","Computer Vision Engineer for Robotics Perception Stack",[39,40,41,42,43,44,45,46,47],"Computer vision","Sensor fusion","LiDAR","Cameras","PyTorch","TensorFlow","Object detection","Tracking","Scene understanding","2026-06-03T06:06:17+00:00",{"id":23,"slug":24,"label":25},{"id":51,"slug":52,"title":53,"skills":54,"budget":16,"duration":16,"location":16,"onsitePercent":16,"contractType":20,"foundAt":63,"category":64},10449,"infrastructure-engineer-for-distributed-model-training","Infrastructure Engineer for Distributed Model Training",[55,56,57,58,59,60,61,62],"PyTorch Distributed","Ray","CUDA","HPC networking","InfiniBand","RDMA","GPU computing","LLM training pipelines","2026-06-03T06:06:04+00:00",{"id":23,"slug":24,"label":25},{"id":66,"slug":67,"title":68,"skills":69,"budget":16,"duration":16,"location":16,"onsitePercent":16,"contractType":20,"foundAt":74,"category":75},10417,"ai-hardware-security-engineer-2","AI Hardware Security Engineer",[70,71,72,73],"Secure firmware","Hardware root of trust","Trusted execution environments","Low-level systems programming","2026-06-03T06:05:34+00:00",{"id":23,"slug":24,"label":25},{"id":77,"slug":78,"title":79,"skills":80,"budget":16,"duration":16,"location":16,"onsitePercent":16,"contractType":20,"foundAt":89,"category":90},10401,"ai-inference-platform-engineer-confidential-computing","AI Inference Platform Engineer - Confidential Computing",[81,82,83,84,85,86,87,88],"Kubernetes","GPU clusters","Confidential computing","Rust","Go","C++","AI inference","ML infrastructure","2026-06-03T06:05:20+00:00",{"id":23,"slug":24,"label":25},{"id":92,"slug":93,"title":94,"skills":95,"budget":16,"duration":16,"location":16,"onsitePercent":16,"contractType":20,"foundAt":104,"category":105},10385,"confidential-ai-systems-engineer-with-tee-expertise","Confidential AI Systems Engineer with TEE expertise",[96,97,98,99,100,101,102,43,57,103],"TEEs","SGX","SEV","TrustZone","Secure boot","Hardware attestation","Confidential containers","AI workloads","2026-06-03T06:05:04+00:00",{"id":23,"slug":24,"label":25},{"id":107,"slug":108,"title":109,"skills":110,"budget":16,"duration":16,"location":16,"onsitePercent":16,"contractType":122,"foundAt":123,"category":124},9009,"senior-npu-kernel-operator-engineer","Senior NPU Kernel \u002F Operator Engineer",[111,8,112,113,114,115,116,117,118,119,120,121],"C\u002FC++","Tensor computation","Neural network operators","Memory hierarchy","Bandwidth and latency analysis","Cache\u002FSRAM behaviour","Parallelism and synchronization","Data locality and vectorization","Performance optimization","Accelerator programming","GPU\u002FNPU development","permanent","2026-06-03T05:31:14+00:00",{"id":23,"slug":24,"label":25},{"id":126,"slug":127,"title":128,"skills":129,"budget":16,"duration":16,"location":145,"onsitePercent":19,"contractType":20,"foundAt":146,"category":147},8140,"ai-and-telco-architect","AI and Telco Architect",[130,131,132,133,134,135,136,137,138,139,140,141,142,143,144],"OSS","Assurance","Fulfillment","Inventory","Fault management","Capacity planning","AI\u002FML technologies","Real-time telemetry","Streaming technologies","Kafka","gNMI","OpenTelemetry","Enterprise architecture","Integration","Stakeholder communication","Netherlands","2026-06-03T05:07:08+00:00",{"id":23,"slug":24,"label":25},{"id":149,"slug":150,"title":151,"skills":152,"budget":164,"duration":16,"location":165,"onsitePercent":166,"contractType":122,"foundAt":167,"category":168},7744,"senior-gpu-systems-ai-infrastructure-engineer-nyc","Senior GPU Systems \u002F AI Infrastructure Engineer (NYC)",[153,154,155,156,86,84,8,43,157,158,159,56,160,161,162,163],"CUDA programming","GPU kernel optimization","parallel computing","distributed systems","JAX","NCCL","MPI","performance profiling","Nsight","Triton","HIP","Competitive + equity","New York City",75,"2026-06-03T04:48:20+00:00",{"id":23,"slug":24,"label":25},{"id":170,"slug":171,"title":172,"skills":173,"budget":16,"duration":16,"location":16,"onsitePercent":16,"contractType":20,"foundAt":178,"category":179},7629,"ai-compute-cluster-engineer","AI Compute Cluster Engineer",[58,81,174,175,176,177],"GPU scheduling","AI compute clusters","networking optimization","storage optimization","2026-06-03T04:37:11+00:00",{"id":23,"slug":24,"label":25},{"id":181,"slug":182,"title":183,"skills":184,"budget":186,"duration":16,"location":187,"onsitePercent":19,"contractType":122,"foundAt":188,"category":189},7608,"ai-telco-architect","AI Telco Architect",[130,131,132,133,134,135,136,137,138,139,140,141,142,185],"Integration experience","up to 90,000 EUR\u002Fyear","Amsterdam","2026-06-03T03:53:26+00:00",{"id":23,"slug":24,"label":25},{"id":191,"slug":192,"title":193,"skills":194,"budget":16,"duration":203,"location":204,"onsitePercent":205,"contractType":20,"foundAt":206,"category":207},7605,"ai-fullstack-engineer","AI Fullstack Engineer",[195,196,197,8,198,9,199,200,201,202],"React","TypeScript","Java","AI\u002FML","AI agents","LangChain","Vector Databases","Fullstack development","Initial 3 Months","Berlin",0,"2026-06-03T03:52:36+00:00",{"id":23,"slug":24,"label":25},{"id":209,"slug":210,"title":211,"skills":212,"budget":222,"duration":16,"location":223,"onsitePercent":16,"contractType":122,"foundAt":224,"category":225},7562,"ai-spezialist-mwd-ai-specialist","AI Spezialist (m\u002Fw\u002Fd) – AI Specialist",[8,213,214,215,216,217,13,218,219,220,221],"R","KI-Tools","Machine Learning","Datenverarbeitung","Cloud-Technologien","Azure","Google Cloud","Datenschutz","Compliance","mindestens 75.000 EUR\u002FJahr","Wien","2026-06-03T00:01:40+00:00",{"id":23,"slug":24,"label":25},{"id":227,"slug":228,"title":229,"skills":230,"budget":16,"duration":16,"location":240,"onsitePercent":241,"contractType":122,"foundAt":242,"category":243},7518,"manager-ki-und-prozessautomatisierung-mwd","Manager KI und Prozessautomatisierung (m\u002Fw\u002Fd)",[231,232,233,234,218,235,236,237,238,239],"KI","Prozessautomatisierung","Microsoft Copilot","Power Automate","ERP-Integration","SAP","Change Management","Digitalisierung","Large Language Models","Stephanskirchen",100,"2026-06-02T14:26:02+00:00",{"id":23,"slug":24,"label":25},{"id":245,"slug":246,"title":247,"skills":248,"budget":16,"duration":261,"location":16,"onsitePercent":262,"contractType":20,"foundAt":263,"category":264},7433,"ai-data-engineer-im-bereich-wissensmanagement-bots","AI Data Engineer im Bereich Wissensmanagement Bots",[249,8,250,251,252,253,254,139,255,256,257,258,259,260,217],"PostgreSQL","ETL\u002FELT-Pipelines","Big Data","SQL","Airflow","dbt","Spark","Data Engineering","Pandas","PySpark","Data Quality","Observability","6M+",20,"2026-06-02T09:30:40+00:00",{"id":23,"slug":24,"label":25},{"id":266,"slug":267,"title":268,"skills":269,"budget":16,"duration":16,"location":223,"onsitePercent":19,"contractType":20,"foundAt":274,"category":275},7414,"machine-learning-engineer-mwd","Machine Learning Engineer (m\u002Fw\u002Fd)",[215,44,43,8,213,270,13,219,271,272,273],"Apache Airflow","Datenmanagement","NLP","Computer Vision","2026-06-02T08:26:02+00:00",{"id":23,"slug":24,"label":25}]