The Role
Develop practical AI solutions using LLMs, Generative AI, AI agents, and RAG. Design prompts, workflows, guardrails, testing plans, and evaluation metrics while integrating models with documents, databases, cloud platforms, and enterprise applications. Collaborate with engineers, architects, and business stakeholders on deployment, monitoring, data preparation, security, and privacy. The role is intended for an early-career candidate with Python programming skills and academic or project experience in LLMs, NLP, or applied machine learning.
Summary Generated by Built In
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
ESSENTIAL SKILLS:
- Foundational knowledge of Large Language Models (LLMs) and how they are used in production.
- Experience with prompt engineering and designing prompt workflows and guardrails.
- Familiarity with Retrieval-Augmented Generation (RAG) concepts and connecting LLMs to documents/databases.
- Basic software development skills (Python preferred) and version control (Git).
- Ability to design and execute test plans for AI systems, including quality and latency measurements.
- Strong analytical and problem-solving skills with attention to detail.
- Clear written and verbal communication skills for working with technical and non-technical stakeholders.
- Knowledge of data handling best practices, security awareness, and privacy considerations.
ADVANTAGEOUS SKILLS:
- Hands-on experience with agent frameworks such as Copilot, LangGraph, or Semantic Kernel.
- Experience implementing RAG pipelines and vector search (e.g., FAISS, Pinecone, Milvus).
- Familiarity with evaluation metrics for LLMs (hallucination measurement, relevance, answer quality).
- Exposure to cloud platforms and deployment tooling (Azure, AWS, or GCP).
- Understanding of MLOps/MLOps-lite practices for model deployment and monitoring.
- Experience integrating AI with enterprise applications (SAP, ServiceNow, SharePoint, Teams).
- Experience with data engineering basics: ETL, data preprocessing and feature extraction.
- Familiarity with automated testing frameworks and CI/CD for AI components.
QUALIFICATIONS/EXPERIENCE:
- Postgraduate degree (Master’s or higher) in Computer Science, Engineering, Statistics or a closely related field.
- Demonstrable coursework, projects, or internships involving LLMs, NLP or applied ML.
- Strong foundational programming skills (Python) and familiarity with AI/ML toolchains and SDKs.
Benefits
- Cutting edge global IT system landscape and processes.
- Flexible working of 1960 hours in a 12-month period.
- High Work-Life balance.
- Remote / On-site work location flexibility.
- Highly motivating, energetic, and fast-paced working environment.
- Modern, state-of-the-art offices.
- Dynamic Global Team collaboration.
- Application of the Agile Working Model Methodology.
Skills Required
- Foundational knowledge of Large Language Models and their production use
- Experience with prompt engineering, prompt workflows, and guardrails
- Familiarity with Retrieval-Augmented Generation and connecting LLMs to documents or databases
- Basic software development skills, preferably Python
- Version control experience with Git
- Ability to design and execute AI system test plans, including quality and latency measurements
- Strong analytical and problem-solving skills with attention to detail
- Clear written and verbal communication skills
- Knowledge of data handling best practices, security awareness, and privacy considerations
- Postgraduate degree or higher in Computer Science, Engineering, Statistics, or a related field
- Coursework, projects, or internships involving LLMs, NLP, or applied machine learning
- Strong foundational programming skills in Python and familiarity with AI/ML toolchains and SDKs
- Hands-on experience with Copilot, LangGraph, or Semantic Kernel
- Experience implementing RAG pipelines and vector search using tools such as FAISS, Pinecone, or Milvus
- Familiarity with LLM evaluation metrics, including hallucination, relevance, and answer quality measurement
- Exposure to Azure, AWS, or GCP and deployment tooling
- Understanding of MLOps or MLOps-lite practices
- Experience integrating AI with SAP, ServiceNow, SharePoint, or Teams
- Experience with ETL, data preprocessing, and feature extraction
- Familiarity with automated testing frameworks and CI/CD for AI components
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The Company
What We Do
Sabenza IT is a niche recruitment company specializing in Information Technology, SAP, Finance, and Engineering roles, with over 23 years of experience.
