AWS AI Cloud Engineer

About the project Join Neurons Lab as a Cloud Engineer on a delivery engagement with a regulated EU BFSI enterprise (German-speaking client). The product is an AI / RAG-based enterprise productivity tool running in production across the client's internal teams. You will pick up a CDK-based codebase already deployed inside the client's AWS account, take over from the outgoing engineer, and own cloud delivery end-to-end: production hardening, security findings remediation, RAG infrastructure stability, and SSO/RBAC integration with the client's identity stack. This is a pure delivery role on a live, customer-managed AWS environment. Data protection is the single most important constraint on every architectural and operational decision. Reporting: AI Architect on the engagement; day-to-day collaboration with the AI Delivery Manager and ML Engineer. Areas of Responsibility - Own and extend the existing AWS CDK codebase deployed inside the client's AWS account. - Operate the production stack: ECS Fargate, ECR, ALB (public + internal), VPC, CDN, S3, AWS Bedrock. - Run the data layer: Postgres, Redis, vector database (Qdrant or similar), LLM observability (Langfuse or similar). - Triage and remediate AWS Security Hub / Health Dashboard findings independently — the client expects us to handle this end-to-end. - Integrate SSO and RBAC with the client's identity stack. - Keep the RAG stack reliable as additional pilot teams onboard; partner with the ML Engineer on retrieval-quality incidents. - Own cost tracking and capacity planning for the client's Bedrock + ECS spend. - Document CDK constructs, runbooks, and incident playbooks so handover to the next engineer takes days, not weeks.