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# Azure AI Cloud Engineer

- **Company:** Fujifilm Holdings America Corporation
- **Location:** Mesa, AZ, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** JavaScript (Programming Language), Artificial Intelligence, ARM Architecture, Microsoft Azure, Cloud Database, Cloud Engineering, Databases, System Configuration, Continuous Integration, Data Integrity, Extract Transform Load (ETL), Data Security, Data Warehousing, DevOps, Python (Programming Language), Machine Learning, Performance Tuning, Query Optimization, Role-Based Access Control, Power BI, SQL Databases, Cloud Platform System, Azure Data Factory, Large Language Models, Snowflake, Generative AI, Semi-structured Data, Infrastructure Automation Frameworks, Information Technology, Machine Learning Operations, Tools for Reporting, Azure AI, Terraform, Azure Synapse Analytics, Data Pipelines
- **Published:** October 2, 2026
- **Apply:** https://dejobs.org/x/x/D862D9965BED48F78ED10E5CB655EB46/job/

## About the Role

* High School diploma or GED and a minimum of 12 years of experience is required.
 * Bachelor's degree in computer science or mathematics and 8 plus years of experience or an AS degree and 10 plus years of experience is preferred.
 * A minimum of 5 years of experience supporting a manufacturing environment.
 * Experience in project management and implementation.
 * Experience with people management/mentorship.
 * Hands-on experience with building AI models in Snowflake.
 * Devops merging and branching knowledge required.
 * PowerBI or similar reporting tool development experience.
 * Experience working with Business Intelligence and Data Warehousing.
 * Proficiency in Microsoft Azure cloud services, and cloud data architectures.
 * Strong hands-on coding skills in Python, SQL, and occasionally JavaScript or Scala.
 * Experience with Azure Synapse, Azure Data Factory, Snowpark, and modern GenAI application stacks (like LangChain or Vector Databases).
 * Familiarity with data modeling, performance tuning (query optimization and warehouse sizing), and data security frameworks.
 * Excellent logical and problem-solving abilities for abstract, creative concepts.
 * Microsoft training and certification will be considered a strong asset.
 * Self-motivated and self-directed.
 * Very high attention to detail.

ADDITIONAL REQUIREMENTS

We value a professional, adaptable, and collaborative work environment. The following competencies are essential for success in any role and reflect our commitment to effective teamwork, problem solving, and workplace communication.

 * Resilience - Ability to adapt to workplace challenges, maintain professionalism, and manage responsibilities effectively.
 * Communication - Capacity to clearly and professionally exchange ideas, interact respectfully with colleagues and customers, and foster positive workplace relationships.
 * Reasoning & Decision Making - Ability to analyze information, follow verbal and written instructions, and make logical, sound decisions.
 * Comprehension - Capability to understand and complete tasks as assigned and solve problems effectively.
 * Organizational Skills - Competence in managing multiple priorities, maintaining accuracy, and staying focused despite potential workplace distractions.

## Description

The Azure AI Cloud Engineer designs, implements, and manages cloud-based infrastructure and services within the Microsoft Azure ecosystem. Provides support in Azure architecture, automation, networking, security, and performance optimization. Implements strong cloud principles, Infrastructure-as-Code (IaC), DevOps methodologies, and enterprise-grade security standards., * AI & ML Integration: Build retrieval-augmented generation (RAG) pipelines and integrate Large Language Models (LLMs) like Snowflake Cortex and Azure AI into enterprise data architectures.

 * Pipeline Development: Design and optimize complex ETL/ELT pipelines for structured and semi-structured data using tools like Azure Data Factory and Snowpipe.
 * Snowflake Platform Administration: Provision and manage Snowflake compute warehouses, ensuring platform security, RBAC (Role-Based Access Control), and cost governance within the Azure environment.
 * Cross-Functional Collaboration: Partner with Data Scientists, MLOps, and business stakeholders to operationalize AI use cases, from proofs-of-concept (POCs) to production scale.
 * Automation & CI/CD: Develop infrastructure-as-code (IaC) and automate workflows using CI/CD pipelines (e.g., Azure DevOps, Terraform).
 * Leadership & Project Management: Lead team coordination between IT functions and manufacturing needs. Manage large projects from concept to full implementation. Manage team members to meet deadlines and milestones.
 * Configuring servers and databases
 * Preserving data integrity