Generative AI Engineer

vor 2 Wochen


Council of the City of Sydney, Österreich N2S.Global Vollzeit

Location: (Insert Location or Remote) Employment Type: Full-time Role Overview We are looking for an experienced Generative AI Engineer to design and implement cutting‑edge AI solutions leveraging LLMs, RAG patterns, and advanced orchestration workflows. This role requires strong expertise in Python, AI/ML frameworks, and cloud‑native architectures, with a focus on building secure, scalable, and innovative AI systems. Key Responsibilities AI/ML Development Build and deploy generative AI models (LLMs such as GPT, Claude) and Retrieval‑Augmented Generation (RAG) pipelines. Frameworks & SDKs Work with LangChain , PyTorch , and OpenAI SDK to develop AI‑driven applications. Workflow Orchestration Design and implement workflows using AWS Step Functions , Temporal , or Flink Services . Cloud Integration Develop and deploy solutions on AWS (Bedrock, Lambda, S3, IAM). Ensure scalability, reliability, and cost optimization in cloud environments. Security & Responsible AI Implement compliance and governance standards for AI systems. Ensure ethical and responsible AI practices in model development and deployment. CI/CD & Observability Build automated pipelines for model deployment and monitoring. Integrate observability tools for performance tracking and anomaly detection. Innovation Experiment with emerging AI technologies and frameworks. Drive research and proof‑of‑concepts for next‑generation AI capabilities. Required Skills & Qualifications Languages: Strong proficiency in Python (primary), Node.js/TypeScript (secondary). AI/ML Expertise: Hands‑on experience with LangChain , PyTorch , OpenAI SDK , and LLM‑based architectures. Generative AI: Deep understanding of LLMs , RAG patterns , and prompt engineering. Cloud & Orchestration: Experience with AWS services and workflow orchestration tools. Security & Compliance: Knowledge of responsible AI principles and governance frameworks. DevOps: Familiarity with CI/CD pipelines and observability tools. Soft Skills: Strong problem‑solving, communication, and collaboration skills. Preferred Experience with vector databases (e.g., Pinecone, Weaviate). Familiarity with MLOps and ModelOps practices. Exposure to multi‑modal AI models and advanced generative techniques. #J-18808-Ljbffr


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