Key Responsibilities

- Build and operate CI/CDintegrated test execution for AI/ML/GenAI workflows across environments • Validate system, integration, and endtoend workflows for AI platforms (agents, APIs, RAG services, model endpoints, pipelines) • Establish test reporting and observability (quality gates, run analytics, pipeline health, deployment risk visibility) • Implement cloud-based AI testing strategies on Azure/AWS, including workplace readiness and service integration checks

- Automate deployment validation including contract testing, dependency checks, and rollback verification • Embed LLMs into CI/CD pipelines for:
- Intelligent test orchestration (prioritization, dynamic suite selection) • Guardrails enforcement (policy checks, response constraints,



safety rules) • Automated compliance & security checks in AI deployments • Partner with platform/SRE/engineering teams to improve reliability using SRE principles (SLIs/SLOs, error budgets, incident learnings) • Support security & compliance awareness through scanning, policy enforcement,

- Must Have Tools • Azure DevOps / GitHub Actions • Cloud AI services (Azure/AWS) • CI/CD test orchestration • API & integration testing tools • Observability dashboards • AWS CloudWatch / Grafana / Prometheus

📌 AI DevOps & Platform QA Engineer (Bangalore) (Bengaluru)
🏢 PwC
📍 Bengaluru