Cloud AI Engineer.
Ideal Candidate Profile (Must-Haves):
- Core AWS Capability: Solid foundational experience in managing core AWS infrastructure (VPC, IAM, Lambda, S3).
- Coding Proficiency: Strong scripting and backend skills in JavaScript/TypeScript (Node.js) or Python.
- AI Curiosity: A strong desire to work with Large Language Models (LLMs) and agentic frameworks.
Key Responsibilities
- Cloud Operations: Maintain core cloud health including compute capacity management, data storage layers, strict IAM access roles, and cost controls for serverless workloads.
- System Integration: Write clean, asynchronous backend logic in JavaScript/TypeScript (Node.js) or Python to connect cloud services with data sources and APIs.
- AI Tooling Deployment: Assist in setting up and managing secure runtime environments for AI agents using Amazon Bedrock AgentCore.
- Workflow Automation: Explore and utilize tools like AWS Kiro to streamline code specifications, automate testing, and sync documentation across codebases.
Core Qualifications
- Cloud Engineering Fundamentals: 2+ years of experience working as an AWS Cloud Engineer or DevOps Engineer. Solid grasp of core infrastructure (VPC, IAM, Lambda, S3, API Gateway).
- Programming: Strong coding proficiency in JavaScript / TypeScript (Node.js) or Python to build data integrations.
- AI Tooling Exposure: Basic familiarity or hands-on interest in working with Large Language Models (LLMs), orchestration frameworks (e.g., LangChain), or prompt configuration.
Preferred Qualifications & Certifications (Added Advantage)
- AWS AI Tools: Prior experience or conceptual knowledge of AWS AgentCore or AWS Kiro.
- Certifications: Any foundational or associate-level AWS Certifications (e.g., Solutions Architect, Developer, AI Practitioner, or Machine Learning Engineer).
