Sébastien Pitt

Profile

Full-stack systems architect and entrepreneur. I accelerate delivery of AI + automation + integrations for customers through an AI-assisted development environment (Cursor, Git) and a modular, reusable, production-ready approach. Now looking to grow within an organization where I can help clients adopt complex solutions and innovate with AI.

Strengths

Connecting client needs & cross-team collaboration: working with client and team to ensure technology adoption.
Need → workshop → demo → proof of value (POV/POC): technical workshops, scoping, success criteria, rapid iterations, documentation, and handoff.
AI use cases: design of AI systems and workflows (e.g., RAG), API-based integration, value measurement (quality, latency, cost).
Platforms: container flow (image → registry → deployment → network exposure → operations), governance, and security.
Integration & automation: workflow orchestration, batch pipelines, Web2/Web3 connectors.

Fundamental Understanding & Hands-on Experiences

Hyperscallers AWS/Azure/Google
Docker/Kubernetes/OpenShift
Container images, registry, deployments, services, network exposure (Route/Ingress), secrets/config, scaling, progressive rollouts
APIs & batch processing (Python, JSON parsing, video encoding, QR generation, endpoints verification, pipelines)
Web3 dApp development (authentication, XMTP wallet messaging, EVM APIs)
Vector stores
Tooling: Git, AI IDE

Professional Experience

Netic Hypermédia inc. — President (2002 – present)

Production leadership and R&D (SR&ED); building scalable solutions and recurring-revenue models (SaaS).
Delivery of process automation solutions and multi-platform integrations.
Rapid prototyping and short cycles: PoC, MVP, pilots, with a delivery- and reusability-driven approach.
Design of automation workflows (data retrieval, scoring, reporting, value realization) and batch pipelines.
Modular, documented approach: integration-ready systems focused on efficiency and robustness.

Netic Hypermédia inc. — Systems Architect (AI-augmented IDE) (2021 – present)

Faster delivery via Cursor AI + Git (prototyping, testing, documentation, iteration).
Applied AI solution design: RAG structures and automation workflows.
Secure API integrations for data analysis and exploitation (e.g., EVM endpoints).

Digital artist & independent researcher (2018 – present)

Generative, interactive, and performative systems (LiDAR installations, AR), distributed at scale.
Automated pipelines (FFmpeg, batch processing, metadata/QR/JSON).
Scaled distribution (Web3): over 300,000 editions collected (NFT) — evidence of technical and operational scalability.

Lecturer — Collège de Maisonneuve (2018 – 2019)

Courses in sound design, digital audio, video editing, visual effects, and encoding.

Education

Master’s in Communication (M.A.), Interactive Multimedia — Université du Québec à Montréal (2003 – 2007)

Projects (POV/POC → adoption format)

1) RAG systems for process learning (SOPs / protocols)

Goal: reduce search time and increase reliability when executing complex procedures.
Approach: corpus structuring, information retrieval design, rapid iterations with criteria (quality, coverage, latency).
Deliverable: structured design and documentation of a reusable, extensible RAG system.

2) Deployment orchestration and modular updates (SaaS)

Goal: speed up deployments and reduce update-related errors.
Approach: standardizing deployment in a clustered environment; automating module-based updates.
Deliverable: pipeline and operational procedures for reproducible deployments.

3) Post-incident audit and recovery (security & resilience)

Goal: restore availability quickly and strengthen the security posture after an incident.
Approach: analysis, hardening, monitoring scripts, and reinforcement.
Deliverable: playbook + control automations to reduce recurrence risk.