Forward DeployedAI Engineer.
Agentic Engineering · Available for remote work
Engagements
End-to-end ownership
I deliver from requirements to production. Architecture, integration, frontend, backend, agent layer, DevOps.
Build or augment with AI
Agentic Systems
Enhance existing products with AI, or deliver new ones. Agents, RAG, knowledge graphs, vision and audio, generative pipelines, private local inference.
- Agents, tooling, skills, MCP, RAG, computer vision, generative AI
- Plugged into your stack or built end-to-end as a new product
- Production-grade output, integration tests included
AI delivery, integrated and tested
Full ownership
Agentic Engineering
I orchestrate coding agents end-to-end, with 15+ years engineering judgment behind it. Architecture, specs, integration tests, security review, and deployment stay in human hands.
- I orchestrate coding agents for compressed, productive delivery
- Specs, integration tests, security review, deployment kept human
- 15+ years engineering judgment behind every commit
Production output, with integration tests
Scoped specialty
Full-Stack Engineer
API integrations, context engineering, performance optimization, automation, frontier-tech stack implementation.
- API integrations and context engineering
- System optimization and automation for manual processes
- Frontier-model integration (SOTA, latest releases)
Scoped delivery, integrated and tested
Productivity multiplier
Accelerated Delivery
Senior engineering at compressed cycles. I orchestrate coding agents to deliver faster, while architecture, integration tests, and security review stay in human hands.
- Compressed cycles, no skipped steps
- Architecture and tests stay human, code generation accelerates
- Specs, integration tests, security review on every commit
Compressed delivery, full engineering rigor
Privacy-first
Private AI Stack
AI that runs on your hardware. Your data never leaves your environment. Containerized inference, reproducible across dev, staging, and production. OpenAI-compatible for drop-in replacement.
- Local inference, no vendor data path
- Containerized and reproducible across dev, staging, and production
- Hardware-flexible inference with OpenAI-compatible APIs
Private inference, runbook included
Best fit
- Founders who want direct technical execution
- Teams with a clear problem and a tight timeline
- Companies hiring for production AI delivery
Not a fit
- Long multi-step interview loops or live coding gates
- Pure research or academic ML profile expectations
- Roles expecting hand-typed code instead of agentic engineering
Experience
15+ Years Shipping
Software engineering background, migrated to fully agentic engineering and AI engineering.
Ohara
Senior AI Solutions Architect
Contract · Remote- Started in prompt and context engineering and expanded into end-to-end AI engineering ownership.
- Built template-first API workflows that improved reliability for generated integrations and reduced failure-prone outputs.
- Implemented MCP and tool-schema integrations across HTTP, SSE, and WebSocket transports.
- Delivered internal AI tools including sprite-sheet generation (single run to 16 assets) and text-to-image-to-3D (GLB) pipeline.
- Built a web3 tool flow for AI-generated Solidity contracts (generate, compile, sign, deploy, return contract address).
- Supported release-critical debugging across templates, integrations, and infrastructure issues.
- Integrated multimodal GenAI APIs across video (Hedra, HeyGen, Luma, Veo 3, Runway), image (GPT-Image, Flux), and audio (ElevenLabs, PlayHT, Lyria 2).
ADGS
Senior Frontend Developer
Full-time · Doha, Qatar- Pandexit: real-time agent-based modeling app with a dynamic Leaflet map, heatmap, AngularJS.
- CARP: Capital Asset Replacement Prediction frontend over a Python predictive-analytics backend.
- STROKK Mobile: biometric verification with a vanilla-JS keyboard capturing per-key timing, pressure, gyroscope, and location.
- Angular 2+ dynamic-form engine, Three.js prototypes, and dockerized AI/NLP API-aggregation prototypes generating PDF reports.
Grupo Ayex
Full-Stack / Game Developer
Full-time · CABA, Argentina- Shipped 2 operational casino games for physical dual-monitor machines with hardware and C# API integration.
- Built a production mobile JavaScript roulette system and additional games.
- Delivered AR/mobile prototypes and full-stack support tooling for event and product flows.
Repos
Selected open-source work
Latest repos on github.com/hec-ovi.
rag-base
RAG API backend, hybrid search (pgvector + ParadeDB BM25 + LightRAG graph), cross-encoder rerank, GLiNER NER, 19 REST endpoints, full integration test suite (115 passing), BGE-M3, Memgraph, Docker.
- RAG
- Hybrid Search
- Knowledge Graph
- ROCm
open-research
Local multi-agent research workflow with planner/finder/summarizer/reviewer/writer agents, session persistence, and cited report export.
- Multi-agent
- LangGraph
- Ollama
- FastAPI
research-skill
Persistent project-scoped knowledge base for Claude Code and other SKILL.md-compatible code CLIs. Progressive disclosure, contrarian-pass investigation, survives context compaction.
- Claude Code
- SKILL.md
- Plugin
- Agent Skills
rebel-forge
Autonomous social-media agent. 11-tool loop with error recovery, 65+ endpoints, local vLLM. Publishes to X, LinkedIn, Facebook, Instagram, Threads from one prompt.
- Autonomous Agent
- vLLM
- Multi-platform
- Self-hosted
vllm-awq4-qwen
Qwen 3.6-27B (AWQ-INT4) on AMD Strix Halo (ROCm 7.13). DFlash drafter for speculative decoding, custom HIP prefill kernel (105-134 t/s flat to 32K), 18 vLLM patches. 24.8 t/s decode, 256K context, vision, tools, Docker.
- vLLM
- Qwen 27B
- AMD Strix Halo
- ROCm
agentickit
Three React hooks (state, actions, forms) to wire an AI copilot into your app. AI SDK 6 native, Zod-typed, optional .pilot/ skills folder. MIT, ~5 kLoC, four runtime deps.
- React
- AI SDK 6
- TypeScript
- MIT
Skills
Delivery Areas
15+ years of practice across these areas. Backed by open-source repos.
Agentic Systems
Multi-agent systems, MCP, agent skills, tool schemas, and context engineering.
- Multi-agent
- MCP
- Agent Skills
- Context engineering
Applied AI
RAG and hybrid retrieval, computer vision, generative AI, multimodal API integration.
- RAG
- Knowledge graph
- Computer vision
- Generative AI
Infrastructure
Docker, local inference, CI/CD, and REST/SSE/WebSocket APIs.
ContainerUP
Hybrid RAGREADY
Private AIACTIVE
API ServerOK
- Docker
- vLLM
- ROCm
- Local inference
Languages & Frameworks
TYTypeScript
JAJavaScript
PYPython
SOSolidity
REReact
NENext.js
THThree.js
PHPhaser
LELeaflet
NONode.js
FAFastAPI
MCMCP
PYPydantic AI
LALangGraph
LALangChain
AIAI SDK
VLvLLM
LLllama.cpp
OLOllama
ROROCm
DODocker
YOYOLO
TYTypeScript
JAJavaScript
PYPython
SOSolidity
REReact
NENext.js
THThree.js
PHPhaser
LELeaflet
NONode.js
FAFastAPI
MCMCP
PYPydantic AI
LALangGraph
LALangChain
AIAI SDK
VLvLLM
LLllama.cpp
OLOllama
ROROCm
DODocker
YOYOLO
Education
Applied AI, IT degree
Selected coursework at IU International University of Applied Sciences, Germany. IT diploma from EET N°468, Argentina.
IU International University
Germany · Remote
Applied AI Coursework
Cloud ProgrammingScore 100%
OOP PythonScore 100%
Cloud ComputingScore 97%
Intro to PythonScore 97%
Computer VisionScore 87%
Computer Vision (Essay)Score 78%
EET N°468
Rosario, Argentina
Personal and Professional Computing
Technical High School Diploma - IT
Cloud Programming
Score 100%Serverless/cloud-oriented implementation patterns.
snakeless
OOP Python
Score 100%Class design, data modeling, and practical OOP structure.
healthhub
Computer Vision
Score 78%Comparative paper: YOLOv8 vs Detectron2 vs EfficientDet, with a custom frame-by-frame analysis frontend.
computer-vision
FAQ
Your questions, answered with clarity
Short answers to help you decide fit and engagement scope quickly.
Contact
Get in touch
Roles, contracts, or technical questions. Direct read within 24-48h.