2 months ago
Bucharest, RomaniaMid Level
Responsibilities
- Build CI/CD pipelines for AI services, prompts, agent configurations, infrastructure, and evaluation assets.
- Automate environment provisioning, testing, deployment, rollback, and release evidence.
- Implement tracing, logging, model and agent monitoring, alerts, and operational dashboards.
- Operationalize evaluation thresholds, incident handling, and continuous-improvement loops.
- Monitor latency, capacity, token usage, infrastructure consumption, cost drivers, model and agent quality, tool failures, retrieval performance, and workflow-level service indicators.
- Define runbooks, service ownership, and production support handover.
- Operate model and prompt assets, agent configurations, evaluation datasets, and release evidence.
- Implement progressive delivery, rollback, secrets management, vulnerability scanning, incident response, and reliability practices for non-deterministic AI systems.
- Support proposals, client workshops, reusable methods and code, coaching, and the practice’s continuous learning agenda.
- Uphold PwC quality, independence, confidentiality, and risk-management requirements.
Requirements
- 4+ years of experience in DevOps, platform engineering, ML engineering, SRE, or cloud operations.
- Strong automation, container, cloud services, observability, and Infrastructure as Code capabilities.
- Experience deploying or operating ML, generative AI, or distributed application workloads.
- Understanding of release controls, reliability, security, and cost optimization.
- Hands-on experience with GitHub Actions, Azure DevOps, GitLab CI, or equivalent, and Terraform, Bicep, or comparable Infrastructure as Code tooling.
- Strong Docker and Kubernetes container and orchestration experience across cloud and hybrid environments.
- Experience with MLflow, platform-native registries, or equivalent lifecycle tooling.
- Practical experience with OpenTelemetry and observability tools such as LangSmith, MLflow, Langfuse, Azure Monitor, Prometheus, or Grafana.
- Experience monitoring AI model and agent quality, tool failures, retrieval performance, latency, token usage, cost, capacity, and workflow-level service indicators.
- Experience with progressive delivery, rollback, secrets management, vulnerability scanning, incident response, and reliability practices for non-deterministic AI systems.
Tech Stack
Categories
About PwC
PwC is a global network of professional services firms providing assurance, tax, and advisory work for businesses and public-sector clients. It sells project-based and managed consulting, audit, and deals services, and implements and integrates business applications. Formed in 1998 by the merger of Price Waterhouse and Coopers & Lybrand, it is headquartered in London and is one of the Big Four accounting firms.