[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-agentic-ai-engineer":3,"similar-agentic-ai-engineer":32},{"id":4,"slug":5,"title":6,"skills":7,"budget":20,"duration":20,"location":20,"onsitePercent":20,"contractType":21,"foundAt":22,"category":23,"description":27,"rawText":28,"webTitle":6,"webText":29,"language":30,"projectId":20,"sourceUrl":31},13025,"agentic-ai-engineer","Agentic AI Engineer",[8,9,10,11,12,13,14,15,16,17,18,19],"LangChain","LangGraph","Python","RAG (Retrieval-Augmented Generation)","LLM","Agent Architecture","Memory Management","Context Management","Tool Integration","Observability","CI\u002FCD","API Integration",null,"permanent","2026-06-15T18:31:34+00:00",{"id":24,"slug":25,"label":26},3,"ai_ml","AI & Machine Learning","Entwicklung von produktionsreifen, intelligenten KI-Systemen mit Fokus auf Agent-Architektur, Orchestrierung, RAG-Pipelines und komplexe Workflows. Die Rolle kombiniert KI-Forschung mit Enterprise-Deployment und erfordert tiefes Verständnis von LLM-Verhalten, Zuverlässigkeit und operativen Constraints.","Agentic AI Engineer About the OpportunityWe're partnering with a globally recognized enterprise organization that is making a significant investment in next-generation AI capabilities and building a world-class AI Engineering function. This team is focused on developing intelligent systems that combine cutting-edge AI research with large-scale enterprise deployment, tackling some of the most challenging problems in reasoning, orchestration, retrieval, memory management, and autonomous workflow execution. As an Agentic AI Engineer, you'll play a key role in designing and building production-grade AI systems capable of reasoning, planning, retrieving information, using tools, and executing complex workflows at scale. You'll work alongside AI researchers, platform engineers, architects, and product leaders to help define how intelligent systems operate within real-world enterprise environments. This is not a prompt-engineering-only role. We are looking for engineers who think deeply about system behavior, context management, grounding, reliability, and how intelligent agents perform under real-world operational constraints. Work You'll DoAs an Agentic AI Engineer, you will design, build, and operationalize LLM-powered systems capable of reasoning, planning, retrieving information, using tools, and executing multi-step workflows reliably at scale. You will work on the \"thinking layer\" of modern AI systems, including:• Agent architecture and orchestration• Tool integration and workflow execution• Retrieval and grounding pipelines• Memory and context management• Evaluation and observability• Reliability, safety, and guardrails You will help shape how complex domain knowledge is transformed into production-grade AI behavior, with a strong emphasis on precision, traceability, maintainability, and operational robustness. Key Responsibilities• Design and implement agentic AI systems capable of multi-step reasoning, planning, tool use, and workflow execution.• Build stateful workflows using frameworks such as LangGraph and LangChain, including branching, retries, self-correction, human-in-the-loop checkpoints, and reusable orchestration patterns.• Develop and integrate Retrieval-Augmented Generation (RAG) pipelines, including ingestion, chunking, embeddings, vector and hybrid retrieval, reranking, contextual compression, and grounding strategies.• Engineer memory and context management capabilities, including conversational state, persistent memory, retrieval-aware context assembly, and token-efficient context engineering.• Build integrations with internal and external tools, APIs, enterprise systems, databases, and model providers so agents can operate safely within real business workflows.• Contribute to context delivery and model interaction patterns that improve how AI systems discover, retrieve, and use relevant information.• Evaluate system quality across both retrieval and generation layers using automated metrics, human review, and task-based evaluation frameworks.• Implement observability for prompts, tool calls, retrieval quality, agent traces, failures, drift, latency, and production behaviour.• Apply guardrails, safety controls, and failure handling mechanisms to improve reliability and reduce hallucinations or unsafe actions.• Stay current on advances in LLMs, agentic systems, evaluation methodologies, and context engineering, translating research and emerging techniques into practical engineering decisions. Required Qualifications• Bachelor's degree in Computer Science, Engineering, Data Science, Computational Linguistics, or a related field.• Hands-on experience building production-grade applications with LLMs, including prompt engineering, tool use, structured outputs, error handling, and model behaviour tuning.• Strong experience with LangChain and especially LangGraph for orchestrating complex LLM workflows and agent behaviour.• Experience designing and optimizing end-to-end RAG systems, including indexing, retrieval, reranking, grounding, and evaluation.• Strong understanding of memory and context management, including context windows, retrieval-driven context assembly, persistent memory, and high-signal context selection.• Deep understanding of LLM behaviour in practice, including strengths, limitations, hallucination risks, reasoning constraints, latency\u002Fcost trade-offs, and evaluation methods.• Strong Python engineering skills and familiarity with modern software engineering practices, including testing, CI\u002FCD, version control, and API integration.• Experience implementing observability, tracing, and debugging for LLM-based systems in production.• Ability to translate ambiguous, high-complexity business processes into robust system logic and reusable AI patterns. Preferred Qualifications• Experience with multi-agent systems and agent collaboration patterns.• Familiarity with vector databases and retrieval infrastructure such as Pinecone, Weaviate, or Milvus.• Exposure to model adaptation and fine-tuning techniques such as LoRA or QLoRA.• Understanding of traditional NLP concepts including tokenization, semantic similarity, entity extraction, summarization, and transformer fundamentals.• Demonstrated habit of staying current with AI research, benchmarks, and emerging engineering patterns.• Experience operating in highly regulated, high-stakes, or operationally complex enterprise environments. The TeamYou will join a multidisciplinary team of AI engineers, platform architects, researchers, and technical leaders building the next generation of enterprise AI systems. The team is focused on solving highly complex real-world challenges where reliability, explainability, scalability, and intelligent decision-making are critical. You'll work on systems that move beyond simple chatbot experiences into sophisticated reasoning, planning, retrieval, and workflow automation capabilities. Success in this role requires a strong engineering mindset, curiosity, and a passion for building the underlying machinery that powers intelligent systems—not just the interfaces users see. Why Apply?• Work on some of the most exciting areas in modern AI, including Agentic AI, RAG, memory systems, orchestration, and reasoning• Help build production-grade AI systems operating at enterprise scale• Collaborate with highly technical engineers, researchers, and architects• Access modern AI tooling, infrastructure, and platforms• Join a rapidly growing AI organization with significant executive sponsorship and long-term investment• Competitive compensation and strong career growth opportunities\nAnsprechpartner: Dominic Holmes\nE-Mail: d.holmes@lawrenceharvey.com","Wir suchen einen erfahrenen Agentic AI Engineer für ein zukunftsorientiertes Projekt bei einer global führenden Unternehmensorganisation. Das Unternehmen investiert massiv in nächstgenerative KI-Fähigkeiten und baut eine erstklassige AI-Engineering-Funktion auf.\n\nIn dieser Rolle werden Sie produktionsreife KI-Systeme entwerfen und entwickeln, die intelligentes Reasoning, Planung, Informationsbeschaffung, Tool-Nutzung und komplexe Workflows in großem Maßstab ermöglichen. Sie arbeiten mit KI-Forschern, Plattform-Ingenieuren, Architekten und Produktleitern zusammen, um intelligente Systeme für echte Enterprise-Umgebungen zu gestalten.\n\nDies ist keine reine Prompt-Engineering-Rolle. Wir suchen Ingenieure, die tiefgreifend über Systemverhalten, Kontextmanagement, Zuverlässigkeit und die Leistung intelligenter Agenten unter realen operativen Bedingungen nachdenken.\n\nIhre Aufgaben umfassen:\n- Design und Implementierung von Agentic-AI-Systemen mit Multi-Step-Reasoning und Workflow-Ausführung\n- Entwicklung zustandsbehafteter Workflows mit modernen Frameworks\n- Aufbau von Retrieval-Augmented-Generation (RAG) Pipelines\n- Engineering von Memory- und Context-Management-Funktionen\n- Integration mit internen und externen Tools, APIs und Enterprise-Systemen\n- Evaluierung der Systemqualität durch automatisierte Metriken und menschliche Bewertung\n\nSie werden an der \"Thinking Layer\" moderner KI-Systeme arbeiten und dabei Fokus auf Präzision, Nachverfolgbarkeit, Wartbarkeit und operative Robustheit legen. Dies ist eine Gelegenheit, intelligente Systeme zu bauen, die echte geschäftliche Herausforderungen lösen.","en","https:\u002F\u002Fwww.lawrenceharvey.com\u002Fde\u002Fjobs\u002F325785agenticaiengineer",{"items":33},[34,53,71,87,102,119,134,151,175,193,208,223,238,252,270],{"id":35,"slug":36,"title":37,"skills":38,"budget":20,"duration":20,"location":20,"onsitePercent":20,"contractType":50,"foundAt":51,"category":52},13024,"llm-modeling-post-training-engineer","LLM Modeling & Post-Training Engineer",[39,40,41,42,43,44,45,46,47,48,10,49],"LLM Fine-Tuning","Supervised Fine-Tuning (SFT)","Reinforcement Learning from Human Feedback (RLHF)","Preference Optimization (DPO, GRPO)","Reward Modeling","LoRA","QLoRA","Model Alignment","Evaluation and Benchmarking","Distributed Training","PyTorch","contracting","2026-06-15T18:26:28+00:00",{"id":24,"slug":25,"label":26},{"id":54,"slug":55,"title":56,"skills":57,"budget":20,"duration":20,"location":67,"onsitePercent":68,"contractType":50,"foundAt":69,"category":70},12923,"ai-prozessingenieur-hardwareentwicklung-mwd","AI Prozessingenieur Hardwareentwicklung (m\u002Fw\u002Fd)",[58,59,60,10,61,62,63,64,65,66],"Informatik","Elektrotechnik","KI-Tools","Machine Learning","MS Azure","SAP","Digitalisierung","Prozessoptimierung","Automatisierung","Erlangen",100,"2026-06-15T12:25:39+00:00",{"id":24,"slug":25,"label":26},{"id":72,"slug":73,"title":74,"skills":75,"budget":20,"duration":82,"location":83,"onsitePercent":84,"contractType":50,"foundAt":85,"category":86},12878,"data-scientist-machine-learning-ki-python-mwd","Data Scientist (Machine Learning, KI, Python) (m\u002Fw\u002Fd)",[10,61,76,77,78,79,80,81],"Data Analytics","Statistik","Artificial Intelligence","Databricks","Azure","Agile Projekterfahrung","Nach Vereinbarung, Start 01.08.2026","Basel",40,"2026-06-15T11:01:17+00:00",{"id":24,"slug":25,"label":26},{"id":88,"slug":89,"title":90,"skills":91,"budget":20,"duration":20,"location":99,"onsitePercent":68,"contractType":21,"foundAt":100,"category":101},12851,"head-of-ai-robotics","Head of AI & Robotics",[92,93,94,61,95,96,97,98],"AI Leadership","Robotics","Autonomous Systems","Software Engineering","Team Leadership","Computer Vision","Technical Strategy","Berlin","2026-06-15T09:45:55+00:00",{"id":24,"slug":25,"label":26},{"id":103,"slug":104,"title":105,"skills":106,"budget":20,"duration":114,"location":115,"onsitePercent":116,"contractType":50,"foundAt":117,"category":118},12678,"ki-trainer-mwd-mit-polnischkenntnissen","KI-Trainer (m\u002Fw\u002Fd) mit Polnischkenntnissen",[107,108,109,110,111,112,113],"Polnisch (Muttersprache oder verhandlungssicher)","Deutsch oder Englisch","KI-Trainings-Erfahrung","Workshop-Moderation","Digitale Trainingsumgebungen (Teams, virtuelle Whiteboards)","Didaktische Erfahrung","Trainingsformate: Impulsvorträge, Workshops, klassische Trainingseinheiten","12 Monate, ab September 2026","Warschau, Polen",30,"2026-06-12T12:55:45+00:00",{"id":24,"slug":25,"label":26},{"id":120,"slug":121,"title":122,"skills":123,"budget":20,"duration":130,"location":99,"onsitePercent":131,"contractType":50,"foundAt":132,"category":133},12492,"business-analyst-im-bereich-ki-governanceki-assistentenentwicklung-mwd","Business Analyst im Bereich KI Governance\u002FKI Assistentenentwicklung (m\u002Fw\u002Fd)",[124,125,126,127,128,129],"Business Analysis","KI Governance","AI Act Regelungsinhalte","KI-Assistenten-Entwicklung","Verfahrensoptimierung","Best Practices KI","3 Monate mit Option auf Verlängerung",20,"2026-06-11T14:28:33+00:00",{"id":24,"slug":25,"label":26},{"id":135,"slug":136,"title":137,"skills":138,"budget":20,"duration":20,"location":147,"onsitePercent":148,"contractType":50,"foundAt":149,"category":150},12487,"it-data-engineer-splunk-mwd","IT Data Engineer Splunk (m\u002Fw\u002Fd)",[10,139,140,79,80,141,142,143,61,144,145,146],"PySpark","Spark SQL","GitLab CI\u002FCD","SQL","ETL","Splunk","REST APIs","Big Data","Hamburg",50,"2026-06-11T14:26:53+00:00",{"id":24,"slug":25,"label":26},{"id":152,"slug":153,"title":154,"skills":155,"budget":20,"duration":170,"location":171,"onsitePercent":172,"contractType":50,"foundAt":173,"category":174},12467,"ai-entwickler-mwd-conversational-ai-mit-cognigy-claude-code-remote","AI Entwickler (m\u002Fw\u002Fd) Conversational AI mit Cognigy \u002F Claude Code - Remote",[156,157,158,159,160,161,162,163,164,165,166,167,168,169],"Conversational AI","Cognigy","Claude Code","Agentic Engineering","Voicebots","Chatbots","Amazon Connect","Amazon Bedrock","AWS","Jira","Confluence","SCRUM","Deutsch","Englisch","Juni\u002FASAP bis 31.12 + Option","München",0,"2026-06-11T13:56:16+00:00",{"id":24,"slug":25,"label":26},{"id":176,"slug":177,"title":178,"skills":179,"budget":187,"duration":188,"location":189,"onsitePercent":190,"contractType":50,"foundAt":191,"category":192},12391,"ki-berater-identifikation-entwicklung-von-ki-use-cases-in-der-energiewirtschaft","KI-Berater – Identifikation & Entwicklung von KI Use Cases in der Energiewirtschaft",[180,181,110,182,61,183,184,185,186],"KI-Beratung","Use-Case-Entwicklung","Projektmanagement","GenAI","Energiewirtschaft","Prozessanalyse","Business Case Entwicklung","max. 70 EUR\u002Fh Remote + 17 EUR\u002Fh Onsite","01.07.2026 - 30.09.2026 (3 Monate)","Regensburg",10,"2026-06-11T09:40:45+00:00",{"id":24,"slug":25,"label":26},{"id":194,"slug":195,"title":196,"skills":197,"budget":204,"duration":20,"location":205,"onsitePercent":148,"contractType":21,"foundAt":206,"category":207},12270,"it-berater-artificial-intelligence-ai-it-consultant-artificial-intelligence-mwd","IT-Berater Artificial Intelligence (AI) \u002F IT-Consultant Artificial Intelligence (m\u002Fw\u002Fd)",[198,80,199,200,201,202,10,203,168,169],"Beratung und Umsetzung von KI-Lösungen","Large Language Models","Prompt Engineering","Azure ML","Cognitive Services","R","bis zu 65.000 EUR Jahresgehalt","Wien","2026-06-11T00:01:43+00:00",{"id":24,"slug":25,"label":26},{"id":209,"slug":210,"title":211,"skills":212,"budget":220,"duration":20,"location":205,"onsitePercent":20,"contractType":21,"foundAt":221,"category":222},12269,"senior-data-scientist-mwd-data-engineer","Senior Data Scientist (m\u002Fw\u002Fd) – Data Engineer",[213,214,10,61,215,97,80,216,164,217,218,219,18],"Data Science","Data Engineering","NLP","Kubernetes","MS SQL Server","PostgreSQL","DevOps","ab 65.000 EUR Bruttojahresgehalt","2026-06-11T00:01:31+00:00",{"id":24,"slug":25,"label":26},{"id":224,"slug":225,"title":226,"skills":227,"budget":20,"duration":20,"location":235,"onsitePercent":148,"contractType":21,"foundAt":236,"category":237},12260,"artificial-intelligence-engineer-insurtech-startup-new-york-hybrid","Artificial Intelligence Engineer | InsurTech Startup | New York (Hybrid)",[10,61,228,229,200,230,49,231,232,216,18,233,215,234],"Generative AI","LLMs","RAG Architectures","TensorFlow","Docker","MLOps","API Development","New York","2026-06-10T19:47:12+00:00",{"id":24,"slug":25,"label":26},{"id":239,"slug":240,"title":241,"skills":242,"budget":20,"duration":20,"location":249,"onsitePercent":68,"contractType":21,"foundAt":250,"category":251},12219,"ai-learning-und-event-manager-mwd","AI Learning und Event Manager (m\u002Fw\u002Fd)",[182,243,228,244,245,246,247,248,168,169],"Event-Management","Microsoft 365","SharePoint","Trainingskonzeption","Moderation","Stakeholder-Koordination","Erlangen, Bayern","2026-06-10T15:27:04+00:00",{"id":24,"slug":25,"label":26},{"id":253,"slug":254,"title":255,"skills":256,"budget":20,"duration":265,"location":266,"onsitePercent":84,"contractType":267,"foundAt":268,"category":269},12121,"ki-entwickler-mwd-gr-frankfurtremote-juli-2026-24-monate","KI Entwickler (m\u002Fw\u002Fd) \u002F\u002F GR Frankfurt\u002Fremote \u002F\u002F Juli 2026 \u002F\u002F 24 Monate",[10,257,258,259,200,260,261,262,263,264],"Java","Generative KI","Chatbot-Entwicklung","RAG Architekturen","GitLab","MCP (Model Context Protocol)","Automatisierte Tests","Deployment Pipelines","24 Monate (Juli 2026 - Juni 2028)","Frankfurt","temp_work","2026-06-10T12:58:09+00:00",{"id":24,"slug":25,"label":26},{"id":271,"slug":272,"title":273,"skills":274,"budget":20,"duration":20,"location":266,"onsitePercent":148,"contractType":50,"foundAt":280,"category":281},12031,"ki-developer-kundenschnittstellen-mwd","KI Developer Kundenschnittstellen (m\u002Fw\u002Fd)",[10,257,258,259,275,200,141,276,277,278,279],"RAG (Retrieval Augmented Generation)","Testing Frameworks","Kanban","Backend-Entwicklung","Frontend-Entwicklung","2026-06-10T09:25:59+00:00",{"id":24,"slug":25,"label":26}]