
Generative Ai Engineer
4 weeks ago
This is a hands-on technical leadership role that combines system architecture, model integration, and team collaboration to bring AI products into production.
Key Responsibilities Lead the design, build, and deployment of AI Agents and multi-component pipelines (MCPs)Architect and implement LLM-based solutions connected to custom datasets using RAG, vector search, and embeddings Work hands-on with ML frameworks such as: ML.
NET, ONNX Runtime, Tensor Flow.
NET, or Python-based libraries (e.g.
Tensor Flow, Py Torch, scikit-learn)Build, train, and deploy models using Azure Machine Learning, Open AI, and Cognitive Services Guide and mentor developers to ensure scalable, production-ready AI delivery Collaborate with cross-functional product and engineering teams in a fast-paced delivery environment Required Experience Demonstrated experience building AI Agents and Multi-Component Pipelines (MCPs)Proven track record connecting LLMs and generative AI to custom datasets (RAG, vector databases, embeddings, etc.)Hands-on experience with ML frameworks/services, including: ML.
NET, ONNX Runtime, Tensor Flow.
NET, or integration with Python ML frameworks Azure Machine Learning, Open AI APIs, and Microsoft Cognitive Services Nice to Have Experience with Lang Chain, Haystack, or MLOps on Azure Familiarity with AI architecture, multi-modal AI, or reasoning systems Strong understanding of production ML systems, including monitoring, scaling, and model lifecycle management Interested? Apply now or get in touch directly with your CV and availability.
We're actively interviewing and ready to move quickly.
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Generative AI Engineer
4 weeks ago
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Generative AI Engineers
4 weeks ago
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Generative AI Engineer
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