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Remote Google Cloud Engineer Jobs in Michigan (NOW HIRING)

NAVA Software Solutions

Cloud Architect - Remote

Lansing, MI · On-site +1

$66 - $84/hr

Experience equivalent to site reliability engineering, DevOps, and/or DevSecOps * Advocates the use ... Google - Professional Cloud Architect * AWS - Solution Architect - Professional * Azure - MCSE:

Ford Motor Company

Data Engineer

Dearborn, MI · On-site +1

$140K - $184K/yr

... Google cloud platform or AI technologies including LLM, Agentic AI, Langchain, or Google ADK. We ... Data Engineer - positions offered by Ford Motor Company (Dearborn, Michigan). Note, this is a ...

Ilitch

Sr. ERP Cloud Application Engineer

Detroit, MI · On-site +1

The Senior ERP Cloud Engineer is responsible for supporting and leading the implementation ... Work is performed primarily in an office or remote environment. The role may include on-call ...

FastTek

DevOps Specialist

Dearborn, MI · On-site +1

$48.50 - $66.50/hr

Google Cloud Platform * IT Operations Skills Preferred: * Dynatrace * Go * Tekton Experience ... Engineer for 99.99% Reliability: Bring a true SRE mindset to our platform. You will design self ...

Integra Partners

Integrations EDI Lead Engineer

Troy, MI · On-site +1

$140K - $140K/yr

Azure /AWS / Google Cloud * Working knowledge of SMART on FHIR, OAuth2, and OpenID Connect * Prior ... Career development opportunities Remote Opportunities We are actively seeking new colleagues in:

Ford Motor Company

Analytics Scientist

Dearborn, MI · On-site +1

$130K - $169K/yr

... engineering from multiple platforms including Google Cloud Platform, Hadoop, Teradata, PC, and Mainframe. 2. Communicating statistical and technical topics to non-technical business partners. 1 year ...

Ford Motor Company

Data Scientist

Dearborn, MI · On-site +1

$107K - $182K/yr

... required: 1. Utilizing Google Cloud platform services for deploying, managing, and scaling ... Engineering, Manufacturing Engineering or a related field and 3 years of experience in the job ...

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All JobsGoogle Cloud Engineer JobsRemote Google Cloud Engineer JobsRemote Google Cloud Engineer Jobs in Michigan

Remote Google Cloud Engineer information

Does Google hire remote Google Cloud engineers?

Google Cloud engineers can work remotely, as Google offers flexible work arrangements for many technical roles, including cloud engineering positions. Remote opportunities depend on the specific role, team, and location requirements, and candidates often need relevant certifications and experience with Google Cloud Platform tools. Job seekers should review individual job postings for remote eligibility and requirements.

What is a remote Google Cloud engineer?

Remote Google Cloud Engineers are IT professionals who design, develop, and manage cloud-based solutions using Google Cloud Platform (GCP) while working from a location outside of a traditional office. Their responsibilities typically include setting up cloud infrastructure, optimizing cloud resources, ensuring security, and supporting deployment of applications on GCP. They collaborate with other team members virtually, using online tools to communicate and manage projects. This role requires expertise in cloud technologies, programming, and a strong understanding of GCP services.

What skills and qualifications are needed to be a remote Google Cloud engineer?

To thrive as a Remote Google Cloud Engineer, you need a strong background in cloud architecture, networking, and programming, usually supported by a degree in computer science or related field and relevant cloud certifications. Familiarity with Google Cloud Platform (GCP) services, infrastructure-as-code tools like Terraform, and DevOps systems such as Kubernetes and CI/CD pipelines is typically required. Excellent problem-solving skills, self-motivation, and effective remote communication are vital soft skills for this role. These abilities ensure secure, scalable cloud solutions and seamless collaboration in distributed work environments.

What is the difference between Remote Google Cloud Engineer vs Remote Cloud Solutions Architect?

AspectRemote Google Cloud EngineerRemote Cloud Solutions Architect
CertificationsGoogle Cloud Certified Professional Cloud EngineerGoogle Cloud Certified Professional Cloud Architect, plus solutions design certifications
Work EnvironmentFocuses on deploying, managing, and optimizing Google Cloud servicesDesigns overall cloud solutions, often overseeing multiple cloud platforms
Employer & Industry UsageTech companies, cloud service providers, enterprises using Google CloudConsulting firms, large enterprises, cloud service providers

The Remote Google Cloud Engineer primarily handles the deployment and management of Google Cloud services, requiring technical expertise in cloud infrastructure. In contrast, the Remote Cloud Solutions Architect designs comprehensive cloud solutions, often across multiple platforms, and focuses on architecture and strategy. Both roles require Google Cloud certifications but differ in scope and responsibilities.

How does a remote Google Cloud engineer collaborate with team members and stakeholders across different time zones?

As a Remote Google Cloud Engineer, you'll frequently work with geographically distributed teams using cloud-based collaboration tools such as Slack, Jira, and Google Workspace. Effective communication and documentation are essential, as you'll often coordinate with developers, project managers, and clients in various time zones. It's common to have flexible meeting schedules and asynchronous workflows to ensure smooth project progress. Cultivating proactive communication habits and clarifying expectations with stakeholders are key to overcoming remote collaboration challenges.

Can a remote Google Cloud Engineer work remotely?

A remote Google Cloud Engineer can work remotely, as many companies in cloud engineering offer fully remote or hybrid positions. Success in remote roles often requires strong communication skills, familiarity with collaboration tools, and relevant certifications like Google Cloud Professional Cloud Engineer. The role typically involves managing cloud infrastructure, deploying applications, and ensuring security from a remote environment.
What are the most commonly searched types of Google Cloud Engineer jobs in Michigan? The most popular types of Google Cloud Engineer jobs in Michigan are:
What are popular job titles related to Remote Google Cloud Engineer jobs in Michigan? For Remote Google Cloud Engineer jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Remote Google Cloud Engineer jobs in Michigan look for? The top searched job categories for Remote Google Cloud Engineer jobs in Michigan are:
What cities in Michigan are hiring for Remote Google Cloud Engineer jobs? Cities in Michigan with the most Remote Google Cloud Engineer job openings:
Remote Google Cloud Engineer jobs near you
Infographic showing various Remote Google Cloud Engineer job openings in Michigan as of August 2026, with employment types broken down into 92% Full Time, 2% Part Time, and 6% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution.

Generative AI Automation Engineer - Remote Job

EnthuZiastic

Flint, MI • Remote

Full-time

Re-posted 16 days ago

Job description

About Us

Our mission is to bring people together and connect them into a community to nurture each other. We aim to share a conducive environment, a joyous space to grow and excel; a world brimming with selfless love and enough kindness. We strive to enrich each of our lives with kaleidoscopic memories we make here - vibrant, lively, of all hues and colors.

Job Description

​

This is a remote position.

We are seeking a highly skilled and innovative Generative AI Automation Engineer to join our team. The ideal candidate will be responsible for designing, developing, and implementing automation solutions powered by Generative AI models. This role requires a combination of expertise in machine learning, natural language processing, software engineering, and automation frameworks to drive efficiency and innovation in business processes.

Key Responsibilities:

Generative AI Model Implementation:

  • Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks.

  • Integrate pre-trained models or build custom models for specific use cases.

Automation Design and Development:

  • Design and implement AI-driven workflows and solutions to automate repetitive tasks and improve process efficiency.

  • Develop APIs, scripts, and tools for seamless integration of AI models into existing systems.

Data Management:

  • Collect, preprocess, and analyze large datasets for training and validating AI models.

  • Ensure data privacy and compliance with regulatory requirements during data handling.

System Integration:

  • Collaborate with software development and IT teams to integrate Generative AI solutions with enterprise systems.

  • Build and maintain pipelines for real-time AI inference and automation.

Monitoring and Optimization:

  • Continuously monitor AI automation solutions to ensure accuracy, efficiency, and reliability.

  • Optimize models and processes based on performance metrics and user feedback.

Research and Innovation:

  • Stay updated with the latest advancements in Generative AI and automation technologies.

  • Identify opportunities for implementing cutting-edge AI solutions to address business challenges.

Documentation and Collaboration:

  • Document technical designs, workflows, and implementation strategies.

  • Collaborate with cross-functional teams, including product managers, data scientists, and software engineers.

Requirements

Required Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

  • Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face.

  • Proficiency in designing and deploying machine learning models, particularly in Generative AI.

  • Experience with automation tools (e.g., RPA, workflow orchestration tools).

  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes).

  • Solid understanding of data structures, algorithms, and software design principles.

  • Strong analytical and problem-solving skills.

  • Excellent communication and teamwork abilities.

Preferred Qualifications:

  • Experience with NLP, image generation, or multimodal AI models.

  • Hands-on experience with APIs for AI services like OpenAI, Cohere, or Google AI.

  • Familiarity with prompt engineering and fine-tuning Generative AI models.

  • Knowledge of MLOps practices for deploying and maintaining AI solutions.

  • Previous experience in automation or workflow optimization projects.

Benefits

Why Join Us?

  • Work with cutting-edge Generative AI technologies.

  • Collaborate with a team of forward-thinking innovators.

  • Make a tangible impact on the future of automation and AI-driven processes.

If you are passionate about leveraging Generative AI to create innovative automation solutions, we invite you to apply and be a part of our dynamic and growing team.

Apply