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# Cloud AI Engineer

- **Company:** Intellectt, Inc
- **Location:** Boston, MA, United States
- **Experience:** Expert
- **Salary:** $124,800 - $135,200
- **Contract:** Contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Application Integration Architecture, Big Data, Cloud Computing, Cloud Computing Security, Cloud Engineering, Continuous Integration, Information Engineering, Data Governance, Data Infrastructure, Data Transformation, Data Stores, Github, Identity and Access Management, Python (Programming Language), Routing, Performance Tuning, Query Optimization, Role-Based Access Control, Cloud Services, Tensorflow, Azure Machine Learning, Search Technologies, SQL Databases, Systems Integration, Tableau (Software), Data Storage Management, Retrieval-Augmented Generation, System Availability, Delivery Pipeline, Large Language Models, Snowflake, Generative AI, Infrastructure as Code (IaC), Amazon Virtual Private Cloud (VPC), Agentic-AI, Cloudformation, Web Filtering, AI Platforms, Infrastructure Automation Frameworks, Information Technology, Route53, Cloudwatch, Model Context Protocol, Amazon Simple Queue Service (SQS), Terraform, Network Server, Data Pipelines
- **Published:** November 11, 2026
- **Apply:** https://www.dice.com/job-detail/b1f6fcbd-e5f2-401e-a0d7-4890649901b6

## About the Role

* Bachelor's degree in Computer Science, Information Technology, Mathematics, or a related discipline.
 * 10+ years of dedicated experience architecting, building, and deploying robust data and cloud solutions on AWS.
 * Demonstrated hands-on experience designing and operating cloud-native Generative AI and production RAG pipelines (vector search, embeddings, document ingestion).
 * Practical experience with Model Context Protocol (MCP), building and integrating MCP servers and client tools for agentic AI architectures.
 * Strong proficiency in Infrastructure as Code (IaC) utilizing Terraform or AWS CloudFormation.
 * Advanced proficiency in Python and complex SQL for data transformation, pipeline development, and AI integration.
 * In-depth Snowflake platform administration experience, including warehouse sizing, performance tuning, and fine-grained data governance.
 * Proven experience with foundational AWS compute and networking (VPC, EKS, EC2, PrivateLink, IAM, Security Groups).
 * Hands-on experience developing CI/CD workflows and automated release testing using GitHub Actions.
 * Practical understanding and implementation of the AWS Well-Architected Framework pillars.
 * Relevant AWS certifications (e.g., AWS Solutions Architect, AWS Machine Learning Specialty, or Data Engineer) preferred.

## Description

Our client is seeking an experienced Cloud AI Engineer with deep expertise across cloud architecture, data engineering, AI/ML frameworks, infrastructure automation, and cloud security. This role is responsible for accelerating enterprise AI adoption by architecting and deploying scalable, secure, and cost-optimized Generative AI solutions-including advanced Retrieval-Augmented Generation (RAG) pipelines, Model Context Protocol (MCP) integrations, and autonomous AI agents. The ideal candidate will bridge data engineering on AWS and Snowflake with modern LLM-driven application workflows, ensuring adherence to the AWS Well-Architected Framework and enterprise-grade security standards., * Architect, build, and deploy enterprise Retrieval-Augmented Generation (RAG) applications using vector databases, embedding models, semantic search engines, and enterprise knowledge repositories.

 * Design, develop, and integrate Model Context Protocol (MCP) servers and clients to establish secure, standardized connectivity between AI agents, LLMs, enterprise APIs, and data stores.
 * Implement robust enterprise AI security, data privacy, and governance frameworks, covering prompt injection mitigation, content filtering, AI Gateway policies, and RBAC across AI services.
 * Optimize generative AI workloads for performance and cost efficiency through model selection, token management, intelligent semantic caching, and latency reduction strategies.
 * Design, build, and maintain large-scale data engineering and analytics pipelines hosted on AWS and Snowflake.
 * Provision and manage cloud infrastructure using Infrastructure as Code (Terraform / CloudFormation) across AWS resources (VPC, EKS, EC2, SNS/SQS, CloudWatch, Route 53, ELB) and Snowflake virtual warehouses.
 * Configure and administer Snowflake environments, ensuring query optimization, storage management, role-based access controls (RBAC), and row/column-level security.
 * Manage secure private networking, routing, and endpoint connections (AWS PrivateLink) bridging AWS services, Snowflake, and Tableau Cloud/Server.
 * Build and maintain automated CI/CD deployment pipelines using GitHub Actions for infrastructure, data pipelines, and application artifacts across multi-environment setups.
 * Troubleshoot complex data platform and model serving incidents, performing root-cause analysis and implementing preventive measures to ensure high availability.