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AI Engineer with less than a year in Generative AI & RAG Architectures
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Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Artificial Intelligence undergraduate student and AI Developer Intern specializing in the Generative AI ecosystem, RAG architectures, and intelligent agent orchestration (LangChain & LangGraph). Experienced in automation, data engineering pipelines, and cloud-based Machine Learning solutions.
UNIMAR
B.S. · Artificial Intelligence
August 1, 2025 – June 30, 2029
Squad AI (Agency Automation)
June 25, 2026 – Present
Architectural design and implementation of a multi-agent framework to automate operations within advertising agencies.
Banking Security Facial Recognition
June 25, 2026 – Present
Programmed a real-time authentication ML pipeline in Python focused on biometric security and fraud reduction.
Urban Mobility Dashboard (Citi Bike NYC)
June 25, 2026 – Present
Interactive Python/Pandas system for geospatial analysis of 104k+ bike trips in NYC using OpenRouteService API, Deck.GL, and Mapbox.
Intelligent RAG Agent
June 25, 2026 – Present
Built state-driven conversational structures via LangGraph for precise and reliable retrieval against external knowledge bases.
AWS Certified AI Practitioner Certification
AWS
January 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a breadth of interests and an ability to apply AI to various domains (urban mobility, banking security, agency automation). The target role of 'AI Engineer' aligns well with the candidate's stated specialization and project experience in Generative AI and ML pipelines. However, the candidate is currently an undergraduate student with limited professional experience, which might impact cultural fit in a senior role requiring extensive industry experience and mentorship.
Soft Skills & Operational Fit
The candidate's resume indicates an ability to work on complex projects and manage full software development lifecycles, suggesting good operational fit. However, without specific assessment data on soft skills like teamwork, problem-solving under pressure, or communication, a comprehensive evaluation is not possible.