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As a Cloud Solution Architect for AI Platforms, you will play a critical role in enabling Hyatt to leverage AI/ML technologies effectively by designing and implementing robust, scalable, and secure cloud-based solutions.
This role requires a deep understanding of both cloud and AI/ML technologies.
As a valued member of the Data Platform Architecture team, you will collaborate with various stakeholders to deliver innovative and efficient AI solutions.
Responsibilities
Architecture & Design: Define scalable, secure, and compliant AI architectures, including AI and data ingestion layers, feature stores, model training clusters, and inference services.
Rapid Prototyping & Demos: Build end-to-end Generative AI and agent-based solutions (LLM-driven chatbots, RAG pipelines, autonomous AI agents) leveraging Streamlit or other UI products for interactive dashboards and demos to showcase value.
MLOps Pipeline Development: Design and implement CI/CD pipelines for data, training, validation, deployment, monitoring, and retraining of ML models (using Git Hub/Gitlab Actions, Jenkins, AWS Code Pipeline, etc.).
Agent Frameworks: Develop and integrate intelligent agent architectures leveraging orchestration platforms (e.g., Lang Chain, Dialog Flow, Tools, MCP's) for multi-agent workflows.
Cloud Engineering: Deploy and manage infrastructure using Ia C (Terraform, Cloud Formation) and container orchestration (Kubernetes, Docker, AWS Services).
Data Engineering:



Build scalable data pipelines (Kafka, Spark, Pub/Sub) and feature stores to support real-time and batch AI workloads.
Security, Monitoring & Governance: Configure IAM roles/policies, security groups, and set up monitoring/alerting (Cloud Logging and Data Dog) and compliance guardrails.
Governance & Best Practices: Establish AI model governance, explainability, and bias-monitoring frameworks.
Model Governance & Evaluation: Define and implement continuous evaluation pipelines to track model performance (accuracy, precision, recall), detect data/model drift, and automate retraining triggers to maintain reliability and compliance.
Knowledge Sharing: Produce architecture blueprints, runbooks, and best-practice guides to upskill teams and shape the product roadmap.
Must-Have Skills & Qualifications
Education & Experience: Master's degree in Computer Science or related field (10+ years of experience may override)
6–8 years of solution architecture experience
Proven track record in AI/ML project delivery (including MVPs)
Experience working in ambiguous, fast-paced environments
4+ years architecting and managing AWS/GCP environments
Deep understanding of AWS services: S3, EC2,



Lambda, RDS, IAM, Kinesis, etc.
Infrastructure as Code: Terraform, Cloud Formation
Strong grasp of networking, policy management, and cloud security
Strong understanding of MLOps pipelines and CI/CD
Experience with agent orchestration frameworks (e.g., Lang Chain, Dialog Flow)
Familiarity with model governance, drift detection, and retraining triggers
Experience building on Snowflake (data warehouse + pipelines)
Knowledge of Kafka, Spark, feature stores
Programming & Tools: Use of Streamlit or similar for UI prototyping and demos
Advanced Education: Ph D or advanced CS degree
Deployment Skills: Experience with canary deployments, A/B testing, and multi-agent workflows
Automation & Monitoring: Deep familiarity with Dev Ops practices, configuration of monitoring/alerting tools like Cloud Logging, Data Dog, and automated retraining and evaluation pipelines
Cross-Platform Experience: Implementing solutions across Windows and Linux OS, on-premises to AWS migration experience
Compensation package
Annual allotment of free hotel stays at Hyatt hotels globally.
A integral family assistance policy with paid time off following the birth or adoption of a child as well as financial assistance for adoption.
Seniority level
Executive
Employment type
Full-time
Job function
Information Technology
Industries
Hospitality
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