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💻 Fullstack AI Engineer Available for Hire
Looking for powerful, production-ready applications that seamlessly leverage the latest AI models? I specialize in:
✅ Multi-Agent Orchestration & Autonomous Workflows (Gemini, OpenAI)
✅ High-Performance Fullstack Web Apps (Next.js 14, React, Vue, Laravel,Python,Go)
✅ End-to-End RAG Pipelines & Semantic Vector Search (Supabase, pgvector)
✅ Scalable DB & Backend Infrastructure (PostgreSQL, AWS, Railway, Docker)
✅ Enterprise Workflow Automation (n8n, webhook architectures)
✅ Advanced Media Processing Pipelines (Self-hosted FFmpeg & BullMQ queues)
My focus is creating clean, resilient, and highly optimized digital systems that actually work in production and automate complex business logic.
📩 Let's collaborate to architect your next intelligent platform and bring your product ideas to life with clean code and cutting-edge AI.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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Hey Contra 👋
Two months ago I posted Promptly here as a work-in-progress and said I'd launch in about three weeks.
Then a health issue knocked me flat, and the three-week plan was gone.
I'm good now — and as of today, the build is done. I just published the full case study as well.
Quick recap: after shipping 20+ projects as a tech lead, I kept watching the same thing break. A founder says one thing, the developer hears another, and a month in, the whole build is based on a misunderstanding nobody caught early.
Promptly closes that gap. You describe your idea in plain English; the AI interviews you, pushes back on the vague parts, and writes a developer-ready spec while you chat.
But the chat is the easy part. The real engineering is everything that stops the AI from being trusted too much:
→ It never touches the database. 16 agents can only propose changes through typed tool calls; backend code checks each one, and invalid calls get rejected and logged.
→ Nothing ever gets lost. It snapshots before anything risky, so you can roll back a single module or the whole project.
→ Spend is capped, always. Every AI call passes four checks before it fires, and each one is logged with its exact cost.
One line sums up the architecture:
The AI proposes. The code decides.
The model gets to be creative. It never gets to be in charge.
Full case study is on my profile, and the product is live if you want to poke at it.
One question:
Shipped anything with LLMs in production? What guardrail saved you — or what missing one burned you?
Every comment on the last post shaped what got built. Thank you for that 🙏
building solo, in public
Any music creators in here? built a free lyric video generator:
https://deadmod.com/studio/
i made the music in the promo, too. MP4 export is surprisingly fast. export srt + timed json. edit lyrics. karaoke lyrics. animated backgrounds. you keep commercial rights. did i mention it's free? like free free.
check it out ya'llll.....
The wavy animated background syncing to the music while also exporting SRT and timed JSON is such a thoughtful combo for creators who need captions elsewhere. Are the backgrounds procedural or shader based, or are you working from a preset library under the hood?
Currently building: Voicecon
An AI voice agent platform. Voice to voice, then voice to action. Agents that hold a real conversation and then actually do the task across your tools.
Status, honestly: voice engine is working. Workflows,
integrations and the app UI are in progress. Domain is live with a waitlist while we finish.
Ruby on Rails backend, multi provider voice orchestration, attachable knowledge bases per agent.
This is my own product. Client work runs through Vconekt, Framer, Webflow, WordPress and Shopify.
