ERNEST GOMES
Dallas, GA | egomes2107@gmail.com
Professional Summary
AI Systems Architect and Prompt Engineer with hands-on experience designing, deploying, and managing multi-model AI orchestration platforms. Built production systems that coordinate 10+ large language models across automated research pipelines, code generation workflows, and real-time data analysis. Specializes in prompt engineering for complex multi-step reasoning, model evaluation and selection, cost optimization across AI providers, and autonomous agent design.
Technical Skills
AI & Prompt Engineering: Multi-model pipeline design, prompt chaining, structured output extraction, model benchmarking and audition frameworks, blind peer review systems, AI-as-judge evaluation, role-specific prompt tuning, context window management, agent orchestration
Models & Platforms: Claude (Opus, Sonnet, Haiku), GPT-4, Gemini Pro/Flash, Grok, Llama, DeepSeek, Perplexity Sonar, OpenRouter, Anthropic API, Google AI API, xAI API
Development & Infrastructure: TypeScript, Node.js, Python, SQLite, REST APIs, Linux server administration, systemd services, cron automation, Cloudflare Workers, Caddy, SSH, Git
Data & Analytics: Real-time data pipeline design, web scraping frameworks, statistical modeling, API integration, database schema design, data freshness monitoring
Projects
AI Orchestration PlatformSolo architect and operator — Production system running 24/7 on cloud infrastructure
- Designed and deployed a multi-model AI orchestration platform that intelligently routes queries across 10+ LLMs based on task type, cost, and capability requirements
- Built a model audition framework that blind-tests 16 candidate models across standardized tasks, scored by independent AI judges, to assign the optimal model to each of 15+ specialized analyst roles
- Engineered a 5-phase advisory council system: question framing, parallel multi-model advisory generation, anonymized blind shuffle, independent peer review, and chairman synthesis — eliminating model bias through procedural design
- Created a multi-stage code generation pipeline where one model writes code, a second performs cold review, and a third conducts final audit — reducing defect rates through adversarial review
- Designed a 6-step research pipeline using model diversity (no model repeated within a pipeline) to produce fact-checked, multi-perspective research briefs
- Optimized API costs by 80%+ through strategic model selection, routing cheap models for simple tasks and reserving expensive models for high-stakes decisions
- Manages 117 automated scheduled jobs across data collection, health monitoring, and analytics
Real-Time Data Intelligence System290+ database tables | 130+ automated data sources | Multi-domain coverage
- Architected a comprehensive data pipeline ingesting real-time pricing, statistical, and sentiment data from 30+ external APIs and web sources
- Built automated data freshness monitoring with stale detection, error tracking, and alerting across all sources
- Designed a 13-desk analytical framework where each desk operates as an independent research unit with specialized AI analysts, dedicated data feeds, and structured output formats
- Implemented automated edge detection algorithms comparing model outputs against market prices across multiple domains
- Created a knowledge graph system linking entities, claims, and research findings with drift detection and version tracking
Tiered Memory Architecture for AI AgentsProduction memory system enabling long-term AI agent coherence
- Built an 11-phase memory system: auto-tagging, vector embeddings, hybrid search, entity versioning, claim tracking with drift detection, proactive recall with dynamic token budgeting, and episodic memory
- Implemented time-based memory tiers (Evergreen, Hot, Warm, Cool, Cold) with configurable decay and token budget allocation, validated through a 5-model panel review
- Designed retrieval-augmented generation (RAG) pipeline using FTS5 full-text search fused with cosine similarity on 384-dimension embeddings
Full-Stack Business Management PlatformComplete web application — Designed, built, and deployed in collaboration with AI
- Directed AI to build a 12-phase business management platform: inventory tracking, grading workflows, order management, financial reporting, customer management, and warehouse fulfillment
- Features include barcode scanning, multi-condition grading, purchase/sale tracking, profit analytics, pick-pack-ship warehouse workflow, and automated reporting
- Full relational database with 20+ tables, REST API backend, and responsive frontend deployed on cloud infrastructure
Multi-Platform Bot Network7 Telegram bots + 5 Discord bots — All running as managed background services
- Built and deployed 12 AI-powered chat bots bridging Telegram and Discord to various LLM backends
- Designed specialized bot roles: general assistant, analyst, tech support, and "fresh-eyes" judges that auto-wipe context between review sessions
- Implemented photo/screenshot OCR, voice transcription, session management, and graceful error handling
Automated Trading SystemsTwo independent algorithmic systems in production
- Designed prompt frameworks for an AI-assisted prediction market trading bot comparing model probabilities against live market prices to identify mispriced contracts
- Built monitoring and alerting for a forex trading system using technical analysis strategies
- Integrated real-time weather forecast APIs and sports data feeds for multi-domain signal generation
AI-Driven Security Audit Framework
- Designed a dual-audit security workflow: one AI model scans for vulnerabilities, a second independent model verifies findings and implements fixes
- Identified and remediated exposed services, overly permissive permissions, prompt injection vectors, and dependency vulnerabilities
Education
Electrical Engineering Certificate
Key Metrics
10+ LLMs orchestrated in production across 5+ providers
290+ database tables across real-time data pipelines
117 automated jobs running on scheduled intervals
13 analytical desks with specialized AI analyst roles
12 chat bots deployed across Telegram and Discord
40+ council sessions run through blind peer review
16 models benchmarked per role in audition framework
80%+ cost reduction through strategic model routing