AI Engineer | IT Ops | 4+ years hardware, software, networks, IoT. Building multi-agent AI on $0 infra. Open to Work — Applied AI/ML Engineer. Remote. 🇯🇲
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
hermes-skills
June 10, 2026 – Present
Open source skills for Hermes Agent. Includes: open-source-contribution workflow (5 phases: discover, scope, write, submit, publish) + multi-platform publishing CLI (Dev.to, GitHub, Mastodon, Bluesky). Submitted to HermesHub.
View Projectrag-eval-system
June 10, 2026 – Present
Production RAG pipeline with LLM-as-judge evaluation. Streaming Q&A, PDF upload, MLflow experiment tracking. 6 tests, all passing. Runs on M1 Mac at /opt/homebrew/bin/bash cloud cost.
View Projectportfolio-agentic-infra
May 31, 2026 – Present
5 production-grade AI agent examples + infrastructure dashboard. All running on free models, /bin/bash/month. Built as portfolio for Applied AI Engineer roles.
View Projecthermes-setup-showcase
May 29, 2026 – Present
AI Agent Infrastructure — Hermes framework, Paperclip multi-agent orchestration, Obsidian knowledge management, 26 cron workflows, 5-layer memory. All running 24/7 on /opt/homebrew/bin/bash cloud.
View ProjectCultural Fit Analysis
The candidate's personal projects demonstrate a strong interest in AI, data engineering, and open-source contributions. The diversity of projects, from RAG systems to AI agent infrastructure and publishing tools, indicates a broad technical curiosity and a drive to build practical solutions. While the target role is 'Frontend Developer', many projects involve backend or full-stack elements (Python, Shell scripting), suggesting a versatile mindset. The emphasis on personal projects and self-learning aligns with a culture that values initiative and continuous improvement. However, direct frontend-specific projects are limited, which might require a cultural fit assessment regarding specialization versus generalization.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and self-directed approach to learning and development, particularly in AI/ML and agent-based systems. The focus on 'production-grade' and 'free models' suggests an awareness of practical constraints and cost-efficiency. However, without psychometric test results or interview data, it is difficult to assess specific soft skills like teamwork, stress handling, or communication clarity in a professional setting.