Senior AI Architect
Siemens Energy Vezi toate joburile
- București
- Permanent
- Full-time
- Design and evolve the core AI infrastructure platform (AWS, Kubernetes, CI/CD, observability) supporting all agents with strict SLAs ??? high uptime, low latency, controlled cost-per-prediction.
- Standardise agent-tool integration using MCP (Model Context Protocol) and production-grade patterns ??? no ad-hoc scripts, no low-code connectors, no brittle REST hacks.
- Build extensible tool and service layers (MCP servers, vector stores, feature stores, auth gateways) that multiple agent teams reuse safely with consistent security, auditing, and performance.
- Lead platform evolution ??? multi-region, zero-downtime deployments, automated cost optimisation ??? so agent teams ship faster without platform bottlenecks.
- Own delivery across multiple concurrent projects and guide a team of engineers, setting technical direction and ensuring consistent quality across workstreams.
- Codify platform patterns into self-service tools (IaC templates, MCP SDKs, deployment playbooks) that reduce onboarding from weeks to hours.
- 5+ years in cloud platform engineering with 2+ years building infrastructure for AI/ML systems at enterprise scale.
- Proven experience leading multiple projects and people simultaneously ??? you've managed delivery across parallel workstreams and mentored engineers to grow.Deep expertise with AWS (ECS, Lambda, API Gateway, Bedrock Agent Core) and infrastructure-as-code (Terraform, CDK) in production environments.
- Experience implementing MCP (Model Context Protocol) or similar agent-tool integration patterns in production ??? not just prototypes.
- Strong knowledge of streaming/real-time infrastructure (Kafka, Redis Streams) and GPU scheduling for inference workloads.
- Production reliability expertise ??? circuit breakers, graceful degradation, chaos engineering, capacity planning ??? for systems where downtime has real consequences.
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