AI-assisted delivery
Equip teams with coding agents, verifiable guardrails and controlled changes before integration.
Mohammed Hamdoune
Founder of LRJI
Staff Software Engineer · Software architecture and AI-assisted delivery
Mohammed Hamdoune, a Staff Software Engineer, helps teams ship faster with AI coding agents without losing control of their architecture: technical leadership, DDD, modernization and GCP platforms.
His profile is deliberately hybrid: framing a CTO can use, Staff-level contribution in the code, and decisions handed over to the team. He delivers with coding agents himself, under guardrails he designed where every change is checked before it is integrated: that is how he builds Emovanti, his own fleet-management SaaS, now preparing its beta.
An architect who stays close to the code
Architecture is valuable only when it changes concrete decisions: boundaries, tests, contracts, pipelines, runtime, ownership and the ability to ship. That is where the engagement sits.
What Mohammed brings
Staff-level technical leadership
Connect decisions, standards and hands-on reinforcement so the team can keep moving independently.
Architecture and modernization
Reduce debt, simplify disproportionate distributed systems and migrate progressively without blocking the product roadmap.
SaaS bootstrap and platform
Lay a TypeScript and GCP foundation ready to ship without building tomorrow's rewrite.
Representative experience
Public references stay discreet, but they show the type of context where the profile is most useful: constrained systems, architecture to clarify and teams to realign.
Retail: 7 microservices to 1 backend
Reduced distributed complexity, one CI flow, 21 pods per environment brought down to 3 and simpler delivery.
Luxury: identity and customer-data flowsCIAM, MDM, Kafka, integration contracts and reliability work in a sensitive distributed ecosystem.
Emovanti: architecture decisions for a multi-tenant SaaSOwn product: ADRs, dated product decisions, and domain guardrails ahead of beta, with no production users.
Decision-oriented engagement
- 01
Read the real system
Codebase, incidents, delivery flow, product constraints, runtime and coordination costs.
- 02
Decide
Name the default decision, accepted risk, rejected alternatives and success criterion.
- 03
Prove it in code
Bring the decision into modules, tests, contracts, pipelines or runbooks.
- 04
Transfer
Make standards explicit so the team keeps autonomy after the engagement.
Where he is most useful
Architecture and delivery
- DDD
- Hexagonal Architecture
- ADRs/RFCs
- C4
- Technical debt
TypeScript engineering
- Node.js
- NestJS
- tRPC
- Vue
- React
- Vitest
Runtime and systems
- GCP
- Cloud Run
- Kubernetes
- Kafka
- RabbitMQ
- PostgreSQL