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Ai Platform Engineer Jobs in Rhode Island (NOW HIRING)

GXO Logistics

Senior DevOps AI Platform Engineer

NC · On-site +1

$130K - $167K/yr

... s AI Platform Engineer Are you ready to take your career to the next level with a rapidly growing global company? As a Senior DevOps Platform Engineer, you will establish and scale the enterprise ...

widenet

AI Platform Migration Engineer

Providence, RI · On-site

$75 - $85/hr

Overview We're looking for a hands-on Migration Engineer to lead our enterprise transition from multiple AI platforms (Claude, ChatGPT, Copilot, and others) onto a single, standardized "golden ...

FM

Lead AI Security Engineer

Johnston, RI · On-site

$121 - $173/hr

The role operates at the intersection of cybersecurity, platform engineering, and emerging AI technologies, supporting enterprise AI solutions such as Microsoft Copilot, Claude, and internally ...

GXO Logistics

Lead AI Application Security Engineer

NC · On-site +1

$59 - $78.75/hr

As the Lead AI Application Security Engineer, you will serve as the technical lead for securing GXO's Enterprise AI Platform and AI-powered applications. You will define AI security architecture ...

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How much do ai platform engineer jobs pay per hour?

As of Sep 1, 2026, the average hourly pay for ai platform engineer in Rhode Island is $62.63, according to ZipRecruiter salary data. Most workers in this role earn between $49.42 and $72.26 per hour, depending on experience, location, and employer.

What is an AI Platform Engineer?

AI Platform Engineers are technology professionals who design, build, and maintain the infrastructure that supports the development, deployment, and scaling of artificial intelligence (AI) and machine learning (ML) models. They work closely with data scientists and software engineers to ensure that AI solutions can run efficiently and securely in production environments. Their responsibilities often include managing cloud or on-premises platforms, automating workflows, and implementing best practices for model versioning, monitoring, and resource optimization.

How does an AI Platform Engineer typically collaborate with data scientists and software engineers in a project environment?

AI Platform Engineers often serve as a bridge between data scientists and software engineers, ensuring that machine learning models are seamlessly integrated into scalable, production-ready systems. They work closely with data scientists to understand model requirements and deployment needs, and with software engineers to embed these models within applications and services. This collaboration involves frequent communication, joint troubleshooting, and participation in code reviews to maintain a robust and efficient AI infrastructure.

What are the key skills and qualifications needed to thrive as an AI Platform Engineer, and why are they important?

To thrive as an AI Platform Engineer, you need strong programming skills (especially in Python and Java), a background in computer science or related fields, and experience with machine learning frameworks. Familiarity with cloud platforms (like AWS, Azure, or GCP), containerization tools (Docker, Kubernetes), and CI/CD systems is typically required, along with certifications such as Google Cloud Professional Machine Learning Engineer. Excellent problem-solving, collaboration, and communication skills help you integrate AI solutions across teams and projects. These competencies ensure the efficient development, deployment, and maintenance of scalable AI systems in dynamic production environments.

What is the difference between Ai Platform Engineer vs Data Engineer?

AspectAi Platform EngineerData Engineer
CredentialsBachelor's in CS, AI, or related; experience with cloud platformsBachelor's in CS, Data Science, or related; experience with databases and ETL tools
Work EnvironmentDeveloping AI infrastructure, deploying ML models, working with cloud servicesBuilding data pipelines, managing data storage, ensuring data quality
Industry UsageTech companies, AI startups, cloud providersFinance, healthcare, e-commerce, any data-driven industry

While both roles involve working with data and cloud platforms, Ai Platform Engineers focus on building and maintaining AI infrastructure and deploying machine learning models. Data Engineers primarily develop data pipelines and manage data storage. The roles often collaborate but serve different core functions within AI and data ecosystems.

How to become an AI platform engineer?

To become an AI platform engineer, you should have a strong background in computer science, software engineering, or related fields, with expertise in machine learning frameworks, cloud computing, and programming languages like Python or Java. Gaining experience with AI tools, data management, and infrastructure deployment is essential, often supported by certifications in cloud platforms such as AWS or Azure. Building a portfolio of projects and staying updated on AI and DevOps practices can also enhance your qualifications.

What does an AI platform engineer do?

An AI platform engineer designs, develops, and maintains the infrastructure and tools needed to deploy and manage artificial intelligence models at scale. They work with cloud services, programming languages, and machine learning frameworks to ensure efficient model training, deployment, and monitoring in production environments.

What is the salary of AI platform engineer?

The salary of an AI platform engineer typically ranges from $100,000 to $150,000 annually, depending on experience, location, and company size. Senior roles or those with specialized skills in cloud platforms and machine learning may earn higher compensation.

What are popular job titles related to Ai Platform Engineer jobs in Rhode Island?

For Ai Platform Engineer jobs in Rhode Island, the most frequently searched job titles are:

What job categories do people searching Ai Platform Engineer jobs in Rhode Island look for?

The top searched job categories for Ai Platform Engineer jobs in Rhode Island are:

What cities in Rhode Island are hiring for Ai Platform Engineer jobs?

Cities in Rhode Island with the most Ai Platform Engineer job openings:

Ai Platform Engineer jobs near you

Senior DevOps AI Platform Engineer

GXO Logistics

NC • On-site, Remote

$130K - $167K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted 8 days ago

GXO Logistics rating

7.2

Company rating: 7.2 out of 10

Based on 242 frontline employees who took The Breakroom Quiz

187th of 366 rated logistics

Job description

Continue to Grow with GXO.
At GXO, we know our greatest asset is people like you - energetic, innovative people of all experience levels and talents who make GXO a great place to work. Your career matters to us because your passion and excitement will help keep our company moving forward.
Senior DevOps AI Platform Engineer
Are you ready to take your career to the next level with a rapidly growing global company? As a Senior DevOps Platform Engineer, you will establish and scale the enterprise DevOps operating model for GXO's Agentic AI Platform. This role is responsible for building secure, automated, and scalable cloud platform capabilities that enable AI application delivery across Google Cloud Platform, Kubernetes, Terraform, and CI/CD ecosystems. You'll partner closely with Cloud Engineering, Platform Architecture, Security, and Product teams to drive developer productivity, platform reliability, and operational excellence. If you're looking for an opportunity to make a significant impact on enterprise AI infrastructure, join us at GXO.
Pay, benefits and more
We are eager to attract the best, so we offer competitive compensation and a generous benefits package, including full health insurance (medical, dental and vision), 401(k), life insurance, disability and the opportunity to participate in a company incentive plan.
What you'll do on a typical day
  • Establish the enterprise DevOps operating model for GXO's Agentic AI Platform, including CI/CD standards, branching strategies, release governance, environment promotion, deployment approvals, and operational handoff practices.
  • Design, build, and manage secure, repeatable CI/CD pipelines supporting AI platform infrastructure, platform services, agents, MCP servers, LiteLLM, Agent Gateway integrations, model-serving components, and supporting services.
  • Engineer, deploy, and operate Kubernetes-based platform capabilities on Google Kubernetes Engine (GKE), including deployment standards, Helm or Kustomize, autoscaling, network policies, workload identity, secrets management, ingress/egress, observability, and production runbooks.
  • Own Terraform infrastructure delivery by developing reusable modules, managing state, enforcing pull request controls, implementing policy guardrails, maintaining environment parity, detecting configuration drift, and promoting infrastructure across development, test, staging, and production environments.
  • Partner with the Principal Cloud Engineer to implement Google Cloud Platform foundations while leading day-to-day DevOps enablement, release engineering, Kubernetes operations, pipeline reliability, and developer experience.
  • Collaborate with the Principal Cloud AI Platform Architect to translate enterprise architecture standards, reference architectures, and architectural decision records (ADRs) into automated build, test, deployment, and operational processes.
  • Enable Phase 2 platform capabilities, including GKE-based open-source model serving, vLLM or comparable inference runtimes, scalable deployment patterns, model tiering infrastructure, and cost-governed platform operations.
  • Implement enterprise DevSecOps controls in partnership with Information Security, including vulnerability scanning, dependency scanning, container image hardening, Binary Authorization (or equivalent), secrets management, audit logging, and secure deployment gates.
  • Create standardized "paved road" developer workflows that enable engineers to provision environments, deploy AI agents, publish MCP services, test integrations, and promote code changes through approved automation.
  • Champion AI-assisted software engineering practices by enabling secure AI coding tools, automated testing, documentation generation, code review acceleration, pipeline diagnostics, and developer productivity improvements.
  • Build comprehensive observability across the platform through logs, metrics, traces, dashboards, alerts, SLOs, SLIs, deployment health monitoring, traceability, cost attribution, and operational readiness reporting.
  • Automate operational processes to reduce manual effort, improve incident response readiness, and maintain runbooks for releases, rollbacks, break-glass procedures, platform operations, and escalation processes.
  • Support secure integration between the AI platform and Snowflake-governed data access patterns through automated deployment, configuration, policy enforcement, and runtime observability.
  • Develop and maintain engineering documentation, including CI/CD standards, Terraform module guidance, Kubernetes operating procedures, release checklists, onboarding documentation, and operational runbooks.

What you need to succeed at GXO
At a minimum, you'll need
  • Bachelor's degree in computer science, Engineering, Information Technology, Cloud Computing, or a related technical field; equivalent hands-on experience may be considered.
  • Google Cloud Professional DevOps Engineer certification required.
  • Minimum of 8 years of platform engineering, DevOps, Site Reliability Engineering (SRE), infrastructure engineering, cloud engineering, or software delivery engineering experience.
  • Minimum of 5 years of hands-on Google Cloud Platform experience supporting production environments.
  • Deep expertise with Google Kubernetes Engine (GKE), including Kubernetes operations, workload identity, networking, autoscaling, ingress/egress, Helm or Kustomize, and production troubleshooting.
  • Expert-level experience developing and managing Terraform infrastructure, including reusable modules, state management, CI/CD integration, policy-as-code, infrastructure promotion, and drift management.
  • Strong experience designing and maintaining secure CI/CD pipelines using Cloud Build, GitHub Actions, GitLab CI, Azure DevOps, Jenkins, or similar platforms.
  • Experience implementing GitOps and DevSecOps practices, including code review automation, dependency scanning, container security, secrets management, signed artifacts, deployment approvals, and security guardrails.
  • Experience supporting cloud-native AI, machine learning, analytics, developer platform, or data platform workloads on Kubernetes and Google Cloud.
  • Ability to collaborate effectively with principal architects, cloud engineers, Information Security, product teams, and software developers to translate architectural vision into production-ready solutions.
  • Strong operational mindset with experience supporting incident response, root cause analysis, observability, production support, SLOs/SLIs, release readiness, and continuous operational improvement.
  • Excellent technical communication skills with the ability to develop engineering documentation, operating procedures, automation standards, and developer guidance.
  • Ability to influence engineering teams across a global matrix organization while driving adoption of modern DevOps and platform engineering practices.

It'd be great if you also have
  • HashiCorp Terraform Associate certification.
  • Certified Kubernetes Administrator (CKA) or Certified Kubernetes Application Developer (CKAD) certification.
  • Google Cloud Professional Cloud Architect, Cloud Security Engineer, or Machine Learning Engineer certifications.
  • Experience with AI platform technologies including LiteLLM, Agent Gateway, MCP servers, Vertex AI, Gemini, model routing, vLLM, or open-source model serving frameworks.
  • Experience enabling AI-assisted software development through secure coding assistants, automated testing, documentation generation, and developer productivity tooling.
  • Strong understanding of secure enterprise AI platform operations, cloud-native architecture, and scalable infrastructure automation.
  • Experience driving platform standardization, operational excellence, and developer enablement across large engineering organizations.
  • Self-starter with the ability to quickly establish credibility, operate independently, and make an immediate impact on the reliability, security, scalability, and velocity of enterprise AI platforms.

We engineer faster, smarter, leaner supply chains.
GXO is a leading provider of cutting-edge supply chain solutions to the most successful companies in the world. We help our customers manage their goods most efficiently using our technology and services. Our greatest strength is our global team - energetic, innovative people of all experience levels and talents who make GXO a great place to work.
We are proud to be an Equal Opportunity employer including Disabled/Veterans.
GXO adheres to CDC, OSHA and state and local requirements regarding COVID safety. All employees and visitors are expected to comply with GXO policies which are in place to safeguard our employees and customers.
All applicants who receive a conditional offer of employment may be required to take and pass a pre-employment drug test.
The above statements are intended to describe the general nature and level of work being performed by people assigned to this classification. They are not intended to be construed as an exhaustive list of all responsibilities, duties and skills required of personnel so classified. All employees may be required to perform duties outside of their normal responsibilities from time to time, as needed. Review GXO's candidate privacy statement here.

What GXO Logistics employees say

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About GXO Logistics

Sourced by ZipRecruiter

GXO Logistics, located in Greenwich, CT, US, is a global leader in the logistics industry. Specializing in innovative supply chain management, it operates across various sectors including e-commerce, food and beverage, technology, and retail. The company has cemented a notable reputation for providing top-notch outsourcing solutions that equip businesses to respond to market changes quickly and efficiently. Originally part of XPO Logistics, GXO, officially separated and spun off as a unique corporation in 2021, taking with it decades of expertise and a robust client roster. Their mission is to propel businesses forward with cutting-edge logistics and transportation solutions while adhering to their core values of safety always, customer-centric, and inclusive.

Industry

Transportation and warehousing

Company size

10,000+ Employees

Headquarters location

Greenwich, CT, US

Year founded

2021

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