AI Engineer | RAG, AI Agents & Multimodal Systems | Ex-Data Analyst (6+ yrs)

AI Engineer with a strong foundation in data analytics and business intelligence, building applied AI systems across RAG, AI agents, and multimodal workflows.
I bring 6+ years of experience in data analytics, reporting, dashboarding, and data quality

• Business Intelligence (BI)
• data engineer
• Datenanalyse
• Microsoft Azure

AI Engineer with a strong foundation in data analytics and business intelligence, building applied AI systems across RAG, AI agents, and multimodal workflows.

I bring 6+ years of experience in data analytics, reporting, dashboarding, and data quality improvement across enterprise, consulting, and research environments. My background in SQL, Python, Power BI, and stakeholder-facing analytics gives me a practical approach to building AI systems that are not only technically sound, but also business-relevant and explainable.

Recently, I completed a full-time, project-based AI Engineering program at Turing College, where I built end-to-end projects in LLM evaluation, Retrieval-Augmented Generation (RAG), LangGraph-based agent workflows, and multimodal AI systems using tools such as Python, FastAPI, LangChain, LangGraph, ChromaDB, and OpenAI APIs.

My work sits at the intersection of structured data, intelligent systems, and workflow automation. I am particularly interested in building AI products that improve decision support, knowledge access, and operational efficiency.

Core areas:
• RAG systems and retrieval pipelines
• AI agents and workflow orchestration
• LLM evaluation and prompt design
• Multimodal AI systems
• Data analytics, reporting, and BI
• AI for decision support and workflow automation

I’m open to opportunities in Applied AI, AI Engineering, Data Analyst and AI-enabled data products.

AI Engineering and LLM Applications
Hands-on experience building applied AI systems with LLMs, prompt engineering, OpenAI APIs, evaluation workflows, guardrails, and structured outputs. Skilled in designing practical AI solutions that are reliable, explainable, and business-relevant.

RAG, Vector Search and Knowledge-Based Systems
Practical experience with Retrieval-Augmented Generation, document ingestion, embeddings, semantic search, vector databases, ChromaDB, and citation-aware AI responses. Able to design RAG pipelines that connect unstructured content with useful, grounded AI outputs.

AI Agents and Workflow Orchestration
Experience building agentic workflows using LangChain and LangGraph, including state handling, clarification loops, conditional logic, tool use, and human-in-the-loop approval steps. Strong interest in practical AI automation and agent-based systems for real business workflows.

Machine Learning and Applied AI
Solid foundation in machine learning concepts, data preprocessing, model-oriented workflows, and applied AI use cases. Experience working with AI-based solutions across analytics, LLM evaluation, RAG assistants, meeting agents, and multimodal content analysis.

Data Analysis, Transformation and Data Quality
Strong expertise in data cleansing, transformation, validation, modeling, and reporting. Experienced in turning complex datasets into clear, actionable insights for business users and non-technical stakeholders. Skilled in improving data quality, standardizing workflows, and reducing manual processing effort through structured analytics solutions.

Programming, Databases and Backend Foundations
Proficient in Python, SQL / T-SQL, data modeling, ETL concepts, and data validation. Practical experience building AI and data-driven applications using Python-based workflows, FastAPI, APIs, and structured backend components.

Business Intelligence, Visualization and Reporting
Advanced experience in Power BI, DAX, dashboarding, KPI frameworks, and management reporting. Skilled in designing dashboards and reports that support decision-making, improve operational visibility, and enable self-service analytics. Experienced in presenting insights to stakeholders and training non-technical users.



Cloud and Microsoft Data Ecosystem
Knowledge of Microsoft Azure, Microsoft Fabric, and cloud-based data solutions. Certified in Microsoft Fabric Analytics Engineering, Power BI Data Analysis, Azure Fundamentals, and Azure Data Fundamentals.

Project Management and Collaboration
Experienced in Agile / Scrum environments, Jira, Git/GitHub, technical documentation, and cross-functional stakeholder collaboration. Reliable in project-based delivery, structured communication, and translating technical concepts into practical business outcomes.

Data Warehousing and Statistical Analysis
Understanding of data warehouse concepts, T-SQL, KPI structures, statistical analysis, and recurring business reporting. Capable of supporting analytical decision-making through structured data models, validation routines, and clear reporting logic.