Operational Capabilities

Designed and deployed a Dockerized multi-service stack with reverse proxy routing to ensure consistent runtime environments across development and production.

Built automated forecasting evaluation pipelines in Python, benchmarking RMSE and MAPE to programmatically select optimal training windows.

Implemented a modular AI-agent orchestration pipeline that ingests financial and news data, generates structured insights, and automates report distribution.

Collected container-level telemetry and log streams to enable anomaly detection and faster root-cause identification.

Engineered structured JSON output layers for LLM systems to support deterministic downstream automation and agent interoperability.

Automated resume and document generation by integrating LLM transformation, YAML structuring, and PDF rendering into a reproducible pipeline.

Deployed and managed multiple MCP servers on a VPS, integrating Grafana dashboards to monitor tool usage, token consumption, and system activity for operational visibility and cost control.

Implemented automated post-restart health validation for Docker containers, triggering urgent alerts if services failed to recover after infrastructure maintenance events.

Configured Fail2ban with custom jail rules to proactively block malicious traffic patterns and dynamically harden server security.

Instrumented VPS-hosted services with container health checks and automated alerting to detect and isolate startup failures after scheduled reboots.

Hardened Linux-based infrastructure using Fail2ban with custom rule sets to dynamically jail high-risk IP behavior patterns.

Deployed Netlify-hosted frontend with Cloudflare Worker integrations to manage edge routing and serverless request handling.

Designed and deployed a Retrieval-Augmented Generation (RAG) pipeline integrating vector databases for semantic search, enabling context-aware LLM responses across structured knowledge bases.

Implemented embedding workflows using transformer models and stored high-dimensional vectors in Qdrant/pgvector, optimizing retrieval latency and relevance scoring for downstream AI agents.

Architected chunking, metadata enrichment, and similarity-ranking strategies to support scalable document ingestion and graph-aligned retrieval for multi-agent reasoning systems.