Azure AI Cloud Engineer

Fujifilm•Mesa, AZ

1d•Onsite

About The Position

FUJIFILM Electronic Materials, U.S.A., Inc., is a global leader in chemical solutions which enable the semiconductor industry and the digital universe. We have an exciting opportunity at our Mesa, AZ facility for an Azure AI Cloud Engineer! 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.

Requirements

High School diploma or GED and a minimum of 12 years of experience is required.
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.
Self-motivated and self-directed.
Very high attention to detail.

Nice To Haves

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.
Microsoft training and certification will be considered a strong asset.

Responsibilities

Build retrieval-augmented generation (RAG) pipelines and integrate Large Language Models (LLMs) like Snowflake Cortex and Azure AI into enterprise data architectures.
Design and optimize complex ETL/ELT pipelines for structured and semi-structured data using tools like Azure Data Factory and Snowpipe.
Provision and manage Snowflake compute warehouses, ensuring platform security, RBAC (Role-Based Access Control), and cost governance within the Azure environment.
Partner with Data Scientists, MLOps, and business stakeholders to operationalize AI use cases, from proofs-of-concept (POCs) to production scale.
Develop infrastructure-as-code (IaC) and automate workflows using CI/CD pipelines (e.g., Azure DevOps, Terraform).
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