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Building MCP reliability infrastructure. Founder @ Giant, Vouqis. I audit production AI agents for silent failure modes
AI is analyzing your overall score…
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Giant
Data Scientist
June 24, 2026 – Present
Vouqis
May 16, 2026 – Present
Reliability Gateway for MCP Servers. Detect null responses, schema mismatches, timeouts, and silent failures before they reach users.
View Projectml-project_implementation
May 1, 2026 – Present
End-to-end supervised regression on 9,535 NYC buildings. IQR outlier removal, log-transform, collinearity pruning → 5-model CV → two-stage hyperparameter search → GradientBoosting MAE 8.6 R2=0.82. Feature importance + surrogate tree + LIME explainability.
View Projectml4sci-gsoc
March 31, 2026 – Present
Jet classification using Autoencoder, GNN and Contrastive Learning for ML4SCI GSoC 2026
View ProjectEntropy_Guard
December 12, 2025 – Present
EntropyGuard: A multimodal AI safety agent that uses Gemini 3 Pro to close the gap between static manuals and dynamic reality. Features AR Ghost Mode, real-time Drift Detection, and neural SOP generation.
View ProjectPersonal_Portfolio
December 7, 2025 – Present
Portfolio showcasing applied AI/ML and LLM engineering work, including end-to-end pipelines, agentic systems, and model deployments. Highlights technical competencies in Python, FastAPI, inference tooling, and cloud services, with projects documented through clear problem–solution–impact narratives.
View ProjectAutonomous-Procurement-AI-System
December 2, 2025 – Present
ProcureGuard: Autonomous Procurement Integrity Agents. A multi-agent system powered by Gemini 1.5 Flash to detect price drift, enforce contract compliance, and automate vendor communication. Built with FastAPI, React, and Python.Topics: agentic-ai google-gemini procurement fastapi react automation
View ProjectSmart-To-Do-Extension
October 28, 2025 – October 28, 2025
Smart-To-Do-Extension — repository
View ProjectCultural Fit Analysis
The candidate's portfolio showcases a strong interest in cutting-edge AI/ML applications, including agentic systems and multimodal AI, which aligns well with innovative and research-driven environments. The diversity of projects, from procurement automation to scientific ML and AI safety, suggests adaptability and a broad intellectual curiosity. The personal nature of most projects indicates self-motivation and initiative. However, without information on collaborative projects or team roles, assessing cultural fit in a team-oriented setting is limited.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex, multi-faceted problems, suggesting strong problem-solving skills. The focus on AI safety and procurement integrity implies an attention to detail and ethical considerations. However, without psychometric test results or interview data, a comprehensive assessment of soft skills, stress handling, and team collaboration is not possible.