Job VC

Our client is a global enterprise software company building an AI-powered, RAG-based documentation platform delivered as production-grade SaaS. The platform is a set of ~10 containerized microservices — predominantly Python, with React front-ends — running fully on Microsoft Azure (App Services, Functions, Data Factory, AI Search, Blob Storage, Key Vault).

The team is hardening the platform for production: consolidating multiple repositories into a single monorepo, standardizing CI/CD, introducing observability and a proper test-automation framework and preparing for multi-region rollout (US, Europe, Asia). The team is heavily AI-assisted, currently producing 15–20 merge requests per week, which makes strong automation and test coverage essential.

You will join as a hands-on engineer embedded in the client's team, attending stand-ups and sprint ceremonies.

Responsibilities:
Design, build, and maintain per-service CI/CD pipelines (GitLab CI today, with a migration to GitHub Enterprise / GitHub Actions in progress)
Support consolidation of multiple repositories into a single monorepo — build orchestration, selective CI triggers, automated builds and testing
Instrument services with Azure Application Insights: dashboards, alerting, synthetic monitoring, and log management
Harden environment promotion (dev → pre-prod → prod), deployments, and secrets management
Deploy and operate services on pre-provisioned Azure resources (provisioning itself is handled by a separate platform team)
Contribute to a reusable automated test framework (unit / integration / E2E) that keeps code-review velocity sustainable under high merge-request throughput
Support security hardening, dependency and vulnerability scanning, and overall production readiness

Requirements:
Strong hands-on Azure experience: App Services, Functions, Key Vault, Storage (Data Factory and AI Search a plus)
CI/CD pipeline design and implementation —
GitLab CI required
; GitHub Actions a strong plus
Solid
Python
(the platform is ~98% Python)
Docker and container best practices
Working knowledge of Infrastructure-as-Code principles (Terraform or Bicep) — enough to deploy reliably onto pre-provisioned infrastructure
Azure observability with
Application Insights
(APM, dashboards, synthetic tests, log management)
Solid English, comfortable collaborating across distributed teams and time zones

Nice to have:
Azure RBAC, Managed Identities, and secrets-management patterns
Monorepo tooling and patterns (build orchestration, selective CI triggers)
Test-automation strategy and framework design (unit → integration → E2E)
Security hardening and compliance practices (vulnerability scanning, dependency auditing / SCA)
Experience in enterprise environments (proxies, SSO, compliance constraints)
Azure Data Factory pipeline development
RAG / AI Search indexing pipelines
Playwright (for synthetic monitoring)
Multi-region / global deployment patterns
Experience working alongside heavy AI-assisted development workflows