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. Own end-to-end cloud delivery for a production AI/RAG tool
2. Work with advanced AWS CDK in a live customer AWS environment
3. Focus on data protection and regulated BFSI enterprise standards
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**
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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**
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* 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**
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* **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**
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* **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**
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* **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.