Baptiste Andre

Backend Developer &

Intervention in setting up AI-based automation workflows, as well as technical modernization and budget optimization of cloud infrastructure.

Implementation of AI automation flows

Design and deployment of automated workflows integrating AI models to make previously manual business tasks reliable and faster

Integration of these flows with existing systems (internal APIs, databases, third-party tools) to ensure end-to-end automation

Implementation of monitoring and error management mechanisms to ensure the reliability of production automations

TypeScript Overhaul

Progressive migration of an existing codebase to TypeScript, with strict typing of critical modules

Refactoring of the project structure to improve maintainability and reduce regressions

Implementation of best practices (linting, API contract typing, testing) to ensure the reliability of future developments

Cloud Cost Optimization

Audit of existing cloud resource usage to identify sources of overconsumption (oversized instances, unused resources, poorly optimized storage)

Implementation of appropriate sizing strategies (scaling, instance selection, storage management) to reduce costs without impacting performance

Technical recommendations and trade-offs to balance cost, performance, and infrastructure reliability

Intervention as a backend and DevOps developer on a system composed of several microservices, with a dual objective: modernizing the existing architecture and ensuring production reliability.

Backend microservices refactoring

Audit of the existing architecture and identification of technical debt points (tight coupling, business logic duplication, lack of clear API contracts)

Progressive refactoring of several Node.js microservices, with separation of responsibilities and clarification of interfaces between services

Implementation of code standards (linting, project structure, error handling) to standardize the codebase across teams

Load optimization

Identification of bottlenecks under heavy load (slow requests, blocking synchronous calls, lack of cache)

Implementation of caching mechanisms, asynchronous queues, and query optimizations to reduce latency and improve throughput

Load testing and resource sizing adjustments (horizontal scaling, connection limit management, pool tuning)

DevOps Interventions

Management and maintenance of the deployment infrastructure (CI/CD, containerization, orchestration)

Interventions on production incidents: diagnosis, remediation, lessons learned to limit recurrence

Improvement of observability (monitoring, logs, alerting) to anticipate problems rather than react to them

Maintenance of the Kubernetes cloud architecture

Developer assistance

Development of internal tools