Software engineer building projects and tools across AI agents, scrapers, platforms, automation, and cloud-backed products.
I also run architecture and technical audits for CAC40 companies and smaller teams, helping them identify bottlenecks, delivery risks, and pragmatic remediation plans.
A practical stack for building AI agents, scrapers, platforms, data pipelines, internal tools, and cloud-backed products.
Experience across product delivery, AI-agent tooling, scraping systems, cloud reliability, and architecture audits for CAC40 and smaller companies.
Built AI-agent tools that combine LLM reasoning, browser automation, memory, vector search, and operator review.
Built pipelines that collect public discussions from Reddit, X, and forums using proxies and headless browsers, then enrich the results into searchable vector databases.
Delivered production systems and architecture audits for public service, CAC40 companies, and smaller teams.
Delivered cloud and frontend solutions for an insurance platform with a focus on reliability, automation, and delivery speed.
Built React + TypeScript interfaces
Architected GCP solutions for data processing
Automated infrastructure with Terraform and CI/CD
Provisioned secure IaaS environments
Selected AI-agent and scraping systems focused on data collection, automation, enrichment, memory, and operational workflows.
A coordinated agent system for TikTok account operations: content research, task planning, browser execution, profile activity, memory, reporting, and human review checkpoints.
A data-intelligence pipeline that scrapes public conversations from Reddit, X, and forums with proxies and headless browsers, enriches the content, and feeds a vector database for research and opportunity detection.
A market-intelligence app that analyzes real user discussions to surface validated business problems and product opportunities.
A roadmap generator that turns vague goals into structured plans with timelines, milestones, and skills to learn.
Need a software engineer for AI agents, scraping infrastructure, platforms, internal tools, or an architecture audit? Let's discuss the workflow and constraints.