Help & Supportcareers@gravityer.com
AI Engineer with less than a year in LLM & Agentic AI Systems
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI Engineer with experience in developing and optimizing LLMs for real-world applications using prompt engineering, instruction tuning, and domain adaptation. Skilled in building Retrieval-Augmented Generation (RAG) systems with FAISS and LangChain, and deploying AI Agents for autonomous reasoning. Proficient in applying PEFT techniques to enhance model accuracy and reduce hallucinations, and integrating LLM-based solutions via REST APIs. Currently pursuing a B.Sc. in Computer Science & Artificial Intelligence with a focus on AI.
Helwan University, Cairo
B.Sc. · Computer Science & Artificial Intelligence
August 1, 2021 – June 30, 2025
Tips Hindawi
GenAI Engineer Intern
July 1, 2025 – November 1, 2025
India
QA System with RAG
June 2, 2026 – Present
Processed uploaded PDFs, split text into semantic chunks, and generated embeddings for contextual retrieval. Implemented embedding-based similarity search integrated with an LLM to produce accurate, grounded answers. Enhanced response relevance and latency through prompt optimization and vector database tuning.
Drug-Drug Interaction (DDI) Prediction System
June 2, 2026 – Present
Built a hybrid AI system combining classical ML and fine-tuned LLMs to predict and explain adverse drug-drug interactions. Designed a two-stage architecture: binary classification for DDI prediction and generative NLP for clinical interpretability. Engineered drug feature vectors from chemical, pharmacological, and structural data sources. Applied PEFT techniques with Hugging Face to fine-tune LLMs efficiently for biomedical text generation. Used schema-guided prompts with OpenAI LLMs to generate structured clinical explanations for polypharmacy scenarios.
Smart Retail Shelf Analyzer
June 2, 2026 – Present
Built an end-to-end computer vision pipeline to detect out-of-stock products and planogram violations on retail shelves in real time. Integrated YOLOv8 for product detection, ByteTrack for multi-object tracking, and PaddleOCR for price label and product name extraction. Used CLIP embeddings to compare live shelf state against reference planogram images and automatically flag misplaced items. Generated bilingual (Arabic/English) shelf audit reports using LangChain integrated with the CV pipeline output. Deployed as a production REST API with FastAPI and Docker; stored historical alerts and analytics in PostgreSQL.
Resume Parsing System
June 2, 2026 – Present
Developed a scalable resume parsing system using LangChain with prompt-conditioned pipelines adaptable across formats and domains. Applied structured output parsers for reliable, schema-driven extraction; deployed via Streamlit.
Automated Video Summarization System
June 2, 2026 – Present
Implemented a pipeline to extract and transcribe speech from video URLs using Whisper. Applied text chunking for efficient token management and LLM-based summarization for concise, context-aware outputs.
Retail Analytics AI Agent
June 2, 2026 – Present
Built a local, free AI agent answering retail analytics questions by combining RAG over documents and SQL over a Northwind SQLite database. Used DSPy to optimize pipeline components and LangGraph for multi-step agent orchestration. Constrained to fully local inference using Phi-3.5-mini-instruct via Ollama – no paid APIs at inference time.
HCIA-AI V4.0
Huawei ICT
June 1, 2026 – Present
Data Engineering
Kiwilytics
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects showcase a strong interest and practical application in various AI domains, including healthcare, retail, and general NLP. This diversity, coupled with an internship focused on GenAI, aligns well with an AI Engineer role. The use of both open-source (Ollama, Hugging Face) and commercial (OpenAI) tools indicates adaptability. However, the lack of professional experience beyond an upcoming internship limits the assessment of long-term cultural fit in a corporate environment.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through complex project implementations. The detailed project descriptions suggest an ability to articulate technical concepts clearly. While the resume highlights technical depth, there is insufficient data to assess stress handling, team collaboration, or specific work attitude beyond project contributions.