AWS AI Cloud Engineer (part-time)

Description

Summary: Join Neurons Lab as a Cloud Engineer to own end-to-end cloud delivery for an AI/RAG-based enterprise productivity tool within a regulated EU BFSI client's AWS environment. Highlights: 1. Pure delivery role on a live, customer-managed AWS environment 2. Focus on production hardening, security, and RAG infrastructure stability 3. Collaborate on cutting-edge AI/GenAI workloads This is a short\-term contract engagement starting May 4, 2025, for a duration of 5 weeks at 0\.3 FTE (approximately 12 hours per week). The schedule is flexible; however, some availability during standard business hours will be required for team syncs and occasional client meetings. **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. **Skills** ---------- * **Advanced AWS CDK** (primary) — must be able to extend an existing CDK codebase from day one, not just author from scratch. * **AWS Bedrock** hands\-on experience — model invocation patterns, IAM scoping, cost monitoring. * **ECS Fargate** in production: task definitions, service auto\-scaling, ALB target groups, blue/green or rolling deploys. * **Networking**: VPC design, public/private ALB patterns, CloudFront, private subnet egress. * **RAG\-stack ops**: deploying and operating a vector database, **Postgres** (RDS/Aurora), **Redis** (ElastiCache), and an LLM observability layer on AWS. * **AWS Security Hub / Inspector / Health Dashboard** — finding triage and remediation in restricted client environments. * **Python** — FastAPI backends, MLOps automation, deployment glue. * **Identity \& access**: SSO (Okta / Azure AD / Cognito), RBAC, IAM least\-privilege design. * **Terraform** — secondary; useful for modules supplied by the client's IT team. * **Working in restricted client AWS accounts** — limited permissions, async approvals, wiki/docs\-portal handovers. * **Communication**: clear written and verbal English. **German is a strong plus**, not required. **Knowledge** ------------- * **AWS Certified Solutions Architect — Associate or Professional** (required), or **AWS Certified DevOps Engineer — Professional**. * Working knowledge of **AWS Well\-Architected** framework, especially Security and Reliability pillars applied to BFSI. * Familiarity with **EU AI Act** obligations relevant to RAG / GenAI products. * **GDPR** fundamentals as they apply to credentials, logs, and EU data residency. **Experience** -------------- * **5\+ years** in cloud / DevOps / cloud engineering, with **2\+ years** of hands\-on AWS CDK in production. * **2\+ years** operating AI/ML or GenAI workloads on AWS (Bedrock, SageMaker, or comparable). * **Direct experience deploying inside a regulated client's AWS account** (BFSI, healthcare, government, or similar) — not just internal sandbox environments. * Track record of stepping into an existing codebase mid\-project and shipping within 1–2 weeks. * Comfortable being the only Cloud Engineer on a small (3–4 person) delivery team.