Title: Cloud Solution Architect (AI focused) Duration: 3 months + extensions Location: Remote (preferably remote in Chicago area) Pay Rate: $85/hr-$100/hr Project: Generative AI project using different AI tools. AI/BI thought spot is the tool, use of snowflake. Core components. Scale to other architecture as well. Not a data science lead, but generative AI with architecture. Not just a data scientist who has developed models. • Architected generative AI based solutions (NLP, Gemini, Open AI) • Cost optimization • System design, functional, non functional • Cloud with AWS and GCP • Generative AI • Architected end to end on a real time app (chatbot, content generation through generative AI, using NLP) • Full experience on open AI models, Gen AI models, architect based on a given solution (scaling on lambda, scale tokens, architecture perspective. • Cost Optimization is a must have, how have you architected to optimize cost if given a model, as they roll out to multiple hotels. Technical must haves: • AI model knowledge • ML model knowledge – Generative AI or AI • Experience architecting • ML Ops, how do you train, test, running on efficient CPUs • Not too technical on data science level, but aware of general technologies on generative AI • Must know how to manage cloud logs, observability for LLMs • Snowflake or any data warehouse for back end data • Build real time scalable applications • Talk about actual use cases • Generative AI models are rapidly changing – what new changes are happening in deep research that you know of with cost controls? How do you cost control deep research to not burn out dollars? Plus: • Hospitality or travel industry • Building agents and optimizing them, how do they use LLMs, how do they connect data and make it private. • How to do you scale efficiently and monitor logs. • Anything with a feature store or AI observatory platforms The Role As an Cloud Solution Architect for AI Platforms you will plays 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 Data Platform Architecture team, you will work in collaboration with various stakeholders to deliver innovative and efficient AI solutions. You’ll help to create solutions to drive the next wave of innovation. You’ll recommend tools and capabilities based on your research of the current environment and knowledge of various on-premises, Cloud-based, and hybrid resources. You’ll work with our engineering, architecture, and migration teams to inform strategy and architecture design. This is an opportunity to stay on top of the latest Cloud resources as you lead efforts to prototype using multiple techniques and new technologies. You’ll be able to broaden your skillset into areas like automation, scripting, and containerization while developing critical systems for several of our internal clients. Join our team as we transform the way we manage data and information by taking advantage of Cloud technology. You will be a part of a ground-floor, hands-on, highly visible team which is positioned for growth and is highly collaborative and passionate about data and data products. We are looking for highly motivated AWS expert who excited about leveraging his skills and his strategic ideas to improve mission execution, who is passionate about creating an amazing user experience that delights end-users and makes their jobs easier. This candidate builds fantastic relationships across all levels of the organization and is recognized as a problem solver who looks to elevate the work of everyone around them. • 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's 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 GitHub/Gitlab Actions, Jenkins, AWS CodePipeline, etc.). • Agent Frameworks: Develop and integrate intelligent agent architectures leveraging orchestration platforms (e.g., LangChain, DialogFlow , Tools , MCP's ) for multi-agent workflows. • Cloud Engineering: Deploy and manage infrastructure using IaC (Terraform, CloudFormation) 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 DataDog) 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. Qualifications Experience Required: • 6+ years in application/platform engineering or analytics; MVPs in AI/ML projects. • 4+ years architecting and managing AWS/GCP cloud environments. • Generative AI and Agent Experience will be must. • Proven track record in ambiguous, fast-paced settings, driving AI/ML and Gen-AI initiatives end-to-end. • Technical Expertise: • Generative AI & Agents: Deep understanding of LLMs, embeddings, vector stores, fine-tuning, and multi-agent orchestration. • MLOps: Hands-on experience with training pipelines, model registries, A/B testing, canary deployments, and monitoring. • Data Platforms: Kafka, Spark, feature stores, and data lakes. • Datastores & Warehousing: Vectorstores ,SQL,noSql,, Redis, Snowflake, • Cloud Infrastructure: IAM, VPC, security groups, PaaS/SaaS performance tuning, and governance. • IaC & CI/CD: Terraform, CloudFormation, GitHub Actions, • Containers & Orchestration: Docker, Kubernetes, AWS Fargate. • Scripting & Automation: Python, Javascript & Typescript ,PowerShell, Bash. • UI Frameworks: Streamlit for building interactive prototypes and dashboards. • 6+ years of experience within the field of application/platform engineering or related technical work including business intelligence, analytics. • 6+ years of experience with AWS Senior Cloud Data Engineering, management, maintenance, or architecting, implementing best practices and industry standards. • Strong knowledge and established experience with AWS services including but not limited to: S3, EC2, RDS, Lambda, Cloud Formation, Kinesis, Data Pipelines, EMR, Step Functions, VPC, IAM, and Security Groups. • Experience with data warehousing platforms such as Snowflake, Redshift or similar. • Experience with DB technologies, programming and scripting (e.g., SQL, Python, PostgreSQL, AWS Aurora, AWS RDS, MongoDB, Redis, ). • Experience with DevOps practices and CI/CD tools, pipelines, and scripting for automation. (GitLab, AWS Code Pipeline tools, Cloud formation and Terraform). • High degree of knowledge in IAM Roles and Policies • Strong knowledge configuring AWS cloud monitoring and alerts for cloud resource availability. • Strong scripting experience using PowerShell and/or Python. • High degree of knowledge in PaaS and SaaS application performance. • Understand enterprise level application architecture diagrams and IT security requirements. • Diagnose and resolve complex cloud issues to maintain high service levels. • Offer persistent technical support and advisement to development teams. • Secondary Responsibilities: • Provide strategic guidance on GenAI solution architecture with the latest design patterns. • Develop and solution architect and scale GenAI applications, focusing on LLMs for innovation. • Serve as GenAI infrastructure advisor for AI-centric applications. • Stay updated with LLM application design patterns for scalability and efficiency. • Lead educational initiatives on GenAI and LLM technologies and perform POC. Compensation: $85/hr to $100/hr. Exact compensation may vary based on several factors, including skills, experience, and education. Benefit packages for this role will start on the 1st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.