I am an entry-level AI Engineer and Machine Learning Developer with practical experience in Python, FastAPI, LLMs including OpenAI and LangChain, and cloud-native systems such as AWS and GCP. I specialize in designing agentic workflows, building Retrieval-Augmented Generation (RAG) pipelines with Neo4j and SQL, and applying advanced prompt engineering techniques to LLM applications across various domains. My hands-on experience extends to integrating Hugging Face NLP models, developing scalable and secure APIs, and deploying ML solutions using major cloud providers. I view AI not just as a problem-solving tool but also as a powerful accelerator for learning and innovation. I rapidly adopt new technologies, prototype solutions, and validate concepts through test-driven experiments. This agile approach helps me iterate quickly and optimize AI systems effectively in production environments, ensuring high-quality, performant, and GDPR-compliant AI deployments.

Benjamin Mutebi

I am an entry-level AI Engineer and Machine Learning Developer with practical experience in Python, FastAPI, LLMs including OpenAI and LangChain, and cloud-native systems such as AWS and GCP. I specialize in designing agentic workflows, building Retrieval-Augmented Generation (RAG) pipelines with Neo4j and SQL, and applying advanced prompt engineering techniques to LLM applications across various domains. My hands-on experience extends to integrating Hugging Face NLP models, developing scalable and secure APIs, and deploying ML solutions using major cloud providers. I view AI not just as a problem-solving tool but also as a powerful accelerator for learning and innovation. I rapidly adopt new technologies, prototype solutions, and validate concepts through test-driven experiments. This agile approach helps me iterate quickly and optimize AI systems effectively in production environments, ensuring high-quality, performant, and GDPR-compliant AI deployments.

Available to hire

I am an entry-level AI Engineer and Machine Learning Developer with practical experience in Python, FastAPI, LLMs including OpenAI and LangChain, and cloud-native systems such as AWS and GCP. I specialize in designing agentic workflows, building Retrieval-Augmented Generation (RAG) pipelines with Neo4j and SQL, and applying advanced prompt engineering techniques to LLM applications across various domains. My hands-on experience extends to integrating Hugging Face NLP models, developing scalable and secure APIs, and deploying ML solutions using major cloud providers.

I view AI not just as a problem-solving tool but also as a powerful accelerator for learning and innovation. I rapidly adopt new technologies, prototype solutions, and validate concepts through test-driven experiments. This agile approach helps me iterate quickly and optimize AI systems effectively in production environments, ensuring high-quality, performant, and GDPR-compliant AI deployments.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Intermediate

Language

English
Fluent
German
Intermediate

Work Experience

AI Engineer Intern – Voice AI Agent Development at Phonx AI Inc.
July 1, 2025 - August 25, 2025
Worked remotely designing and optimizing a Voice AI Agent system to achieve high LLM output accuracy and sub-second latency (<1500 ms) in real-time phone conversations. Focused on agentic workflows, Retrieval-Augmented Generation optimization using Neo4j Vector Knowledge Graph, and speech intelligence while ensuring GDPR compliance, data security, and scalability. Achievements included improving RAG search accuracy by 26.8%, increasing Mistral-7B LLM decision accuracy from 63% to 100%, introducing Model Context Protocol for multi-tenant memory management, reducing inference latency by 500 ms, and engineering a custom Voice Activity Detection system with up to 98.5% speech detection accuracy. Integrated hybrid transcription pipelines and deployed open-source LLM benchmarks on AWS.
Aerospace Engineering Intern at Academic Project
December 31, 2021 - August 25, 2025
Conducted aerospace systems simulations using MATLAB/Simulink and COMSOL. Applied procedural programming techniques for structural analysis which laid an early foundation for modeling and AI experimentation.

Education

Bachelor of Science in Software Engineering at University of Europe for Applied Sciences
January 1, 2022 - August 1, 2025

Qualifications

Add your qualifications or awards here.

Industry Experience

Software & Internet, Professional Services, Education, Healthcare, Other

Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Intermediate