We’re looking for an enthusiastic AI Engineer to join a forward-thinking global technology environment where you’ll work on real-world AI solutions, experiment with emerging technologies and help turn exciting AI concepts into practical business applications.

This is a fantastic opportunity for someone early in their AI career who wants exposure to Large Language Models, Generative AI, AI Agents and Retrieval-Augmented Generation (RAG) while working alongside experienced AI engineers, architects and business teams.

Requirements

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  Foundational knowledge of Large Language Models (LLMs) and how they are used in production.
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  Experience with prompt engineering and designing prompt workflows and guardrails.
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  Familiarity with Retrieval-Augmented Generation (RAG) concepts and connecting LLMs to documents/databases.
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  Basic software development skills (Python preferred) and version control (Git).
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  Ability to design and execute test plans for AI systems, including quality and latency measurements.
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  Strong analytical and problem-solving skills with attention to detail.
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  Clear written and verbal communication skills for working with technical and non-technical stakeholders.
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  Knowledge of data handling best practices, security awareness, and privacy considerations.

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  Hands-on experience with agent frameworks such as Copilot, LangGraph, or Semantic Kernel.
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  Experience implementing RAG pipelines and vector search (e.g., FAISS, Pinecone, Milvus).
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  Familiarity with evaluation metrics for LLMs (hallucination measurement, relevance, answer quality).
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  Exposure to cloud platforms and deployment tooling (Azure, AWS, or GCP).
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  Understanding of MLOps/MLOps-lite practices for model deployment and monitoring.
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  Experience integrating AI with enterprise applications (SAP, ServiceNow, SharePoint, Teams).
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  Experience with data engineering basics: ETL, data preprocessing and feature extraction.
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  Familiarity with automated testing frameworks and CI/CD for AI components.

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  Postgraduate degree (Master’s or higher) in Computer Science, Engineering, Statistics or a closely related field.
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  Demonstrable coursework, projects, or internships involving LLMs, NLP or applied ML.
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  Strong foundational programming skills (Python) and familiarity with AI/ML toolchains and SDKs.

Benefits

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  Cutting edge global IT system landscape and processes.
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  Flexible working of 1960 hours in a 12-month period.
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  High Work-Life balance.
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  Remote / On-site work location flexibility.
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  Highly motivating, energetic, and fast-paced working environment.
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  Modern, state-of-the-art offices.
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  Dynamic Global Team collaboration.
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  Application of the Agile Working Model Methodology.