Senior Platform Engineer: AI Delivery & Reliable CI/CD

About Us

Rejoins WeScale et contribue à un accompagnement de haut niveau pour structurer, orienter et accélérer les transformations technologiques de nos clients.

The Context

The AI-augmented squads at WeScale only stand if the ground beneath their feet is solid. CI/CD pipelines integrating agents, infrastructure reproducible from one client to another, system observability where part of the deliverables are generated by LLMs — this is a platform scope that didn't exist two years ago. You will build it.

If you want to continue managing infra without engaging with this change, this is not the right place. If you are curious about what this concretely implies in terms of pipelines and reliability, it is.

You will design and operate the platform that runs the Augmented Software Factory: CI/CD pipelines where agents participate in review and validation steps, cloud-native infrastructure reproducible via IaC, end-to-end observability — including on AI outputs (drift, latency, quality of generated deliverables). You will define infrastructure blueprints that squads reuse from one client engagement to another. You will work in close proximity with the delivery squads and the AI Architect. You are not in an ops ivory tower — you are in the delivery loop.

Your Role as a Consultant at WeScale

• You join a dynamic community of enthusiasts and have the opportunity to play a key role in the company's life.
• You participate in WeShare, a day per month dedicated to knowledge sharing.
• You can explore internal roles such as Manager, Mentor, Technical Recruiter, Offering Lead, or Tooling Builder.
• You leverage your expertise by contributing internally through articles, conferences, and feedback.

WeScale finances your training and certifications to enable you to progress continuously.

Key Areas of Growth

• Regular skill development on AI technologies, particularly LLMs and agents.

Technical Skills & Experience

• Platform Engineering, DevOps, or SRE: 8+ years of experience on cloud-native systems in production. You've seen pipelines fail in production and know why. A true reliability culture — SLOs, error budgets, post-mortems, toil reduction. Not an incident response culture, but a culture of preventing incidents.
• AI Curiosity: Genuine curiosity for AI in pipelines. You don't need to be an LLM expert, but you must understand what it means to have an agent in a CI/CD loop: non-determinism, cost, observability of outputs.
• Blueprint Design: Ability to structure reusable blueprints. What works for one client should be reproducible for the next in a day, not two weeks.
• Mentorship: Pedagogical skills. You guide dev squads in adopting best practices — Shift Left, immutable infrastructure, canary deployments — without blocking them.

Desired Technical Skills

• Kubernetes & Containers: Mastery of the Kubernetes ecosystem (Helm, Kustomize, operators), Docker, management of namespaces and network policies. Multi-cluster experience is a plus.
• CI/CD & GitOps: GitHub Actions, GitLab CI, or Jenkins — design of complex pipelines including automated validation steps. ArgoCD or Flux for GitOps orchestration.
• Infrastructure as Code: Terraform as a priority, Ansible for configuration. You think in terms of reusable modules, not one-shot scripts.
• Cloud: Expertise in at least one hyperscaler (AWS, GCP, or Azure) — networking, IAM, managed services, cost. Certification is a plus, practice is paramount.
• Observability: Complete stack of logs/metrics/traces — Prometheus, Grafana, ELK, or Loki, OpenTelemetry. Definition of SLOs/SLIs for systems integrating non-deterministic AI components.
• SecOps / DevSecOps: Vulnerability scanning in pipelines (Trivy, Snyk, or equivalents), secrets management (Vault, AWS Secrets Manager), Least Privilege policy, compliance-as-code.
• MLOps: Knowledge of deploying and monitoring models in production — artifact versioning, drift detection, inference endpoint management. Concrete experience, even on a personal project, is valued.
• Scripting & Automation: Python, Go, or Bash for advanced pipeline automation and internal tooling construction.