AWS Quick & Generative AI Specialist

About USEReady

USEReady is a leader in modern analytics, AI, and cloud engineering solutions. Our flagship product, Pixel Perfect, enables enterprise-grade, pixel-perfect reporting for modern analytics platforms. As we continue to scale globally, we are looking for an experienced AWS DevOps engineer to build, automate, secure, and operate our cloud-native SaaS platform.

This role offers the opportunity to work on cutting-edge AWS technologies, modern DevSecOps practices, AI-powered engineering, and enterprise-scale cloud infrastructure while contributing to next-generation AI-driven modernization initiatives.

Role Overview

We are looking for an experiencedAWS Quick Specialist with strong hands-on expertise in designing, implementing, and deliveringAmazon Quick solutions for enterprise customers. The ideal candidate will combine deep Quick expertise with strong knowledge ofAWS Analytics, Generative AI and Agentic AI services to help customers modernize their BI and analytics landscape.

This is a hands-on role requiring someone who haspersonally implemented Amazon Quick in real-world enterprise environments, not just conceptual or pre-sales exposure.

Key Responsibilities

• Design and implementAmazon Quick dashboards, analyses, datasets, semantic models and enterprise BI solutions.

• LeadBI modernization and migration initiatives from platforms such as Tableau, Power BI or other legacy BI technologies to Amazon Quick.

• Work with customers to translate business and analytical requirements into scalable AWS-native solutions.

• Develop reusable frameworks, accelerators and best practices for Amazon Quick implementations.

• Integrate Amazon Quick with AWS data services includingAmazon Redshift, Athena, S3, RDS, Glue and other AWS analytics services.

• ApplyGenerative AI and Agentic AI capabilities to analytics and BI use cases.

• Work hands-on withAmazon Bedrock, foundation models, knowledge bases, agents and enterprise AI patterns.

• Develop or contribute to solutions leveragingAmazon Quick Desktop / Quick capabilities and emerging AWS AI/analytics services.

• Gain working knowledge ofAmazon Bedrock AgentCore and agentic application architectures.

• Collaborate with Solution Architects, Data Engineers, AI Engineers and customer stakeholders to deliver production-grade solutions.

• Support customer workshops, technical demonstrations, PoCs and solution design activities.

Must-Have Skills

• 8–10 years of overall technology experience.

• Strong hands-on experience with Amazon Quick is mandatory.

• Proven experience implementingAmazon Quick for enterprise customers — candidates with only training, certification or theoretical knowledge will not be suitable.

• Strong understanding of BI, analytics, dashboards, data visualization and semantic modeling.

• Hands-on experience with AWS analytics services such asRedshift, Athena, S3, Glue and RDS.

• Strong understanding of cloud-based data and analytics architectures.

• Experience with at least one enterprise BI platform such asTableau, Power BI, Qlik or similar.

• Strong customer-facing communication and solutioning skills.

AI / GenAI Skills — Strong Advantage

• Amazon Bedrock — hands-on knowledge of foundation models, Knowledge Bases, Agents and GenAI application patterns.

• Understanding ofAgentic AI architectures and autonomous AI agents.

• Exposure toAmazon Bedrock AgentCore and related agent development/orchestration capabilities.

• Experience integrating GenAI into analytics, BI or enterprise applications.

• Knowledge of RAG, embeddings, vector databases and prompt engineering.

• AWS Certified AI / Machine Learning certification or equivalent demonstrated expertise.

Preferred Certifications

• AWS CertifiedAI Practitioner / Machine Learning Engineer / Machine Learning Specialty

• AWS Certified Solutions Architect – Associate/Professional

• AWS Certified Data Engineer – Associate

• Relevant Amazon Quick / AWS analytics certifications or demonstrated equivalent expertise.

What Success Looks Like

The successful candidate will become ago-to technical expert for Amazon Quick and AWS-native analytics, capable of independently leading customer discussions, architecture, PoCs and implementations while bringingGenAI and Agentic AI capabilities into modern analytics solutions.

Key differentiator: Deep, provenhands-on Amazon Quick implementation experience is the primary selection criterion.