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Portrait of Mohamed Douaré (Mohamed Douare), DevOps and AI platform lead

DevOps & AI Platform Lead

I'm Mohamed Douaré. I lead DevOps, security and AI platform work, and I build AI-native systems that organizations can trust in production: multi-agent systems and agentic workflows, constrained by design.

Mohamed Douaré's path, 2013 to today: from software engineer to DevOps and AI platform lead From software engineer to DevOps and AI platform lead CURRENT TITLE DevOps & AI Platform Lead CLÉ, Ottawa · Director of IT, CIAUD 2013 - 2018 Foundations THE WORLD Cloud still young; information security becomes a business language ROLE Applied maths degree, Oujda State engineer, FST Mohammedia WHAT I GAIN Formal rigour Algorithms, SQL, systems Information security 2017 - 2019 Shipping THE WORLD Web and mobile apps explode; organisations want tools, not slides ROLE Software engineer ONEE, Morocco WHAT I GAIN Business apps, national utility Delivery under real constraints ISO 27001, risk analysis 2019 - 2021 Cloud and DevOps THE WORLD Cloud migration, remote work; data becomes an asset ROLE DevOps engineer, CIAUD Gulpes founder, M.Sc. UQO WHAT I GAIN CI/CD, automated deployments End-to-end mobile product Azure, Entra ID, data 2021 - 2023 Platforms and IaC THE WORLD Anti-Racism Act, 2017; Law 25; PIPEDA: compliance from the design stage ROLE DevOps & software engineer, CLÉ Cloud & systems engineer, CIAUD WHAT I GAIN SGDI: identity census for 13 Ontario school boards Azure and M365 as code (Terraform) 2023 - 2025 Leading IT THE WORLD Platform engineering, dataops: ship fast without breaking security ROLE Director of IT, CIAUD CTO and co-founder, Ciney Labs WHAT I GAIN DevOps, dev and AI teams; Aria Gestra: Prefect, dbt, PostgreSQL Secure inter-client exchanges 2025 - today DevOps and AI platform THE WORLD LLMs in production, agents, MCP: the job is to govern the chain ROLE DevOps & AI Platform Lead, CLÉ Director of IT, CIAUD WHAT I GAIN Multi-agent systems, 17 repos AI usage policy, security program Model proposes, system verifies Technical base → cloud and DevOps → leading DevOps, security and AI Mohamed Douaré's path, 2013 to today: from software engineer to DevOps and AI platform lead From software engineer to DevOps and AI platform lead CURRENT TITLE DevOps & AI Platform Lead CLÉ, Ottawa · Director of IT, CIAUD 2013 - 2018 Foundations THE WORLD Cloud still young; information security becomes a business language ROLE Applied maths degree, Oujda State engineer, FST Mohammedia WHAT I GAIN Formal rigour Algorithms, SQL, systems Information security 2017 - 2019 Shipping THE WORLD Web and mobile apps explode; organisations want tools, not slides ROLE Software engineer ONEE, Morocco WHAT I GAIN Business apps, national utility Delivery under real constraints ISO 27001, risk analysis 2019 - 2021 Cloud and DevOps THE WORLD Cloud migration, remote work; data becomes an asset ROLE DevOps engineer, CIAUD Gulpes founder, M.Sc. UQO WHAT I GAIN CI/CD, automated deployments End-to-end mobile product Azure, Entra ID, data 2021 - 2023 Platforms and IaC THE WORLD Anti-Racism Act, 2017; Law 25; PIPEDA: compliance from the design stage ROLE DevOps & software engineer, CLÉ Cloud & systems engineer, CIAUD WHAT I GAIN SGDI: identity census for 13 Ontario school boards Azure and M365 as code (Terraform) 2023 - 2025 Leading IT THE WORLD Platform engineering, dataops: ship fast without breaking security ROLE Director of IT, CIAUD CTO and co-founder, Ciney Labs WHAT I GAIN DevOps, dev and AI teams; Aria Gestra: Prefect, dbt, PostgreSQL Secure inter-client exchanges 2025 - today DevOps and AI platform THE WORLD LLMs in production, agents, MCP: the job is to govern the chain ROLE DevOps & AI Platform Lead, CLÉ Director of IT, CIAUD WHAT I GAIN Multi-agent systems, 17 repos AI usage policy, security program Model proposes, system verifies Technical base → cloud and DevOps → leading DevOps, security and AI

Scroll sideways to read the whole path.


Products I launched


Skills

AI & agents: Claude, GPT, Gemini and Grok APIs (structured outputs, prompt caching, PDF and document understanding), Claude Code (custom skills, subagents, Remote Control, review loops), Model Context Protocol (Figma, GitHub, Azure DevOps, Todoist), model-proposed plans with tested verification, Deepgram speech-to-text, cost governance and evaluation

Cloud: Azure (App Service, Front Door + WAF, Cosmos DB, Service Bus, Key Vault, Static Web Apps, Entra ID, Communication Services), AWS, Google Cloud, Microsoft 365

IaC & CI/CD: Terraform, Ansible, Docker & Docker Compose, Kubernetes, Azure Pipelines, GitHub Actions, Git, deployment automation, OIDC and managed identities, PM2, Caddy, Linux, server patch management, mobile release automation (TestFlight, Google Play)

Product & data: TypeScript, Python, Dart; Next.js, NestJS, Hono, Flutter, Expo / React Native, Electron; PostgreSQL (Drizzle, Prisma), MongoDB / Cosmos DB, MSSQL; Prefect, dbt, Power BI

Security & compliance: OAuth2 / OIDC, MFA, RBAC, immutable audit trails, envelope encryption, ISO 27001 practices, Law 25 / PIPEDA, Anti-Racism Act, 2017 (identity-based data collection), WCAG 2.1 AA


Signature systems

AI Product Factory

An idea leaves in the morning, a reviewed pull request comes back the same day. A server runs continuously and puts agents to work across 17 GitHub and Azure DevOps repositories: they research the market, write the requirements, design in Figma or Claude Design, build tests first, review each other and open the pull request. I keep two decisions: what gets specified, and what reaches production. A bilingual corporate site shipped in 8 days, a five-application platform in 10 weeks.

A human only at the gates: the agents keep the pace, I keep the accountability for what ships.

Read the architecture →

Aria: funding-opportunities engine

A funder publishes a call with its own Word and Excel forms. The engine reads the call, works out the form cell by cell, then writes the answer straight into it, leaving the styles and the budget formulas intact. Every passage is schema-checked, costed, and comes with the points a reviewer should verify. Anything the organisation never wrote down stays a blank to fill, never an invented sentence. A reviewer takes over and submits.

Structured output rather than a chatbot: the deliverable is the funder's file, not text to copy over.

Read the architecture →

Pilume: AI-proposed medication schedules

A Quebec pharmacist opens a patient's file and asks for their medication schedule. The model reads the clinical picture, proposes the day hour by hour, writes the sentence the patient will read and flags what deserves a second look. A tested verifier then says what is wrong without correcting anything. The model sees no name and no identifier, and nothing reaches the patient without the pharmacist's approval.

The model proposes, the system verifies, the pharmacist decides: safety rests on that gate and the audit log, not on trusting the model.

Read the architecture →

Aria: integrated management platform

The platform that runs an NGO working in several countries (CIAUD): staff, contracts, leave, projects, tenders, stock, tickets and e-signature, in one bilingual application. 18 modules, 13 roles, 6 releases shipped, hosted on Azure and deployed automatically on every merge.

Next.js · MongoDB / Cosmos DB · Azure · Terraform · Claude API

Data platforms for CLÉ

The Anti-Racism Act, 2017 required every Ontario school board to collect identity-based and race-based data before January 2023. SGDI is the platform that made it possible for 13 of them, with the level of security that kind of data demands. Gestra, for its part, pulls operational data out of several clients' databases, cleans it and prepares it for their dashboards.

Python · Prefect · dbt · Ansible · Power BI · Azure

Embertree and the Gulpes app

Embertree keeps a family spread across countries around the same tree: everyone adds photos, tells a story out loud and finds it transcribed. Nothing is public, and each family holds its own encryption key. Gulpes is the personal-development app I launched in 2019, on iOS and Android, with articles, audio and subscriptions.

Next.js 15 · Hono · Drizzle / PostgreSQL · Expo · Flutter · Firebase

Also: bilingual corporate websites on Azure Static Web Apps and GitHub Pages for CIAUD, Blitz IT, Liptako Mining Services, Ciney Labs and 3dk Consulting, each provisioned with Terraform and shipped through CI/CD.


How I govern AI in production

Contracts, not text: structured outputs validated against a schema on every call; the model fills a locator, the rendering layer owns the document.

Cost and model policy: prompt caching, token and cost accounting per file, a model chosen per task, and a tested verifier between the model and the human.

Privacy by construction: de-identification at the source, no identifiers in prompts, an immutable audit log on every access to sensitive data.

Policy and program: I own the AI usage policy and the security program at CLÉ, so the rules agents and people follow are written down before they are enforced.

Humans where it counts: mandatory review before anything leaves the organisation, and two things I refuse to automate: promotion to production and validation of the business act (pharmacist, proposal reviewer).

Regulated ground: AI and data platforms under Law 25 / PIPEDA and provincial standards for Ontario education (13 school boards under the Anti-Racism Act, 2017), Quebec community pharmacy, non-profits and international funders: RBAC, envelope encryption, WCAG 2.1 AA, ISO 27001 practices.

A harness, not trust: development agents work in an isolated worktree, never see secrets or production data, can only merge to the dev branch, stop on command, and every change is a reviewed pull request in the client's own git history. Read the guarantees →


Logo Gulpes Logo Gulpes Self Development Logo Ciney Labs Logo CLE Logo CIAUD Logo Onee Logo Blitz

Send me an email about your project and I will schedule a meeting for it.