AI engineering graduate building multi-agent systems, LLM evaluation pipelines, and production AI tooling. Based in Gold Coast, Australia — open to graduate AI/ML engineering roles in 2026.
- Multi-agent AI systems — autonomous pipelines with role-separated agents (Researcher, Analyst, Writer, Critic) using LangChain and OpenAI
- LLM evaluation & reliability — automated scoring pipelines to benchmark agent accuracy, latency, and failure modes
- Production MCP servers — Model Context Protocol servers integrating AWS S3, DynamoDB, Slack, and JWT auth for real-world data annotation workflows
AI/ML: OpenAI API · LangChain · Streamlit · MCP Protocol · Ollama
Cloud/Infra: AWS S3 · DynamoDB · Vercel
Tools: Git · VS Code · Cursor IDE · Docker
| Project | Description | Stack |
|---|---|---|
| ai-email-assistant | Multi-agent email triage, draft & reply pipeline — WIL industry project | Python · OpenAI · LangChain |
| agent-eval-pipeline | Automated evaluation & reliability scoring for LLM agents | TypeScript · OpenAI |
| multi-agent-research-assistant | 4-agent research report pipeline with Critic revision loop & Streamlit UI | Python · LangChain · Streamlit |
| custom-mcp-server | Production MCP server — S3, DynamoDB, Slack, JWT auth | TypeScript · AWS · MCP |
Bachelor of Computer Science (Data Science focus) — Griffith University · GPA 5.1 · Graduating June 2026
- LinkedIn: linkedin.com/in/satyam-sharma
- Email: Satyamsh04@gmail.com

