Website Vultr
The AI-first Global Cloud Platform
Quick Job Snapshot
Company: Vultr
Job Type: Full-Time
Location: Remote (United States)
Department: Engineering
Salary: $110,000–$140,000 per year
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About the Company
Vultr is a global cloud infrastructure provider delivering scalable cloud computing, GPU, storage, and bare metal solutions to organizations around the world. With cloud locations spanning multiple continents, the company helps businesses, developers, and AI innovators deploy applications and services closer to their users.
As one of the largest privately held cloud infrastructure companies, Vultr continues to invest heavily in cloud computing, artificial intelligence, and developer-focused technologies designed to support the next generation of software innovation.
About the Role
Vultr is seeking a Senior AI Platform Engineer to help build and scale the internal AI infrastructure that powers software development workflows across the organization.
This role combines software engineering, AI infrastructure, cloud technologies, and developer productivity. You will work closely with engineering teams to integrate AI-powered capabilities into development environments, automate repetitive tasks, and create systems that help engineers build software more efficiently.
The ideal candidate has hands-on experience with large language models (LLMs), AI infrastructure, cloud-native technologies, and software development practices. This position offers the opportunity to influence how AI is integrated into engineering operations at scale.
Key Responsibilities
AI Platform Development
- Evaluate and deploy open-source AI models for engineering use cases
- Build and maintain AI infrastructure supporting internal development teams
- Optimize model performance, routing strategies, and deployment processes
- Manage the lifecycle of AI models from testing through production deployment
- Benchmark model performance against real-world engineering workloads
Developer Productivity & AI Integration
- Integrate AI capabilities into software development workflows
- Implement AI-powered code review, testing, and documentation processes
- Build tooling that improves developer efficiency and productivity
- Create reusable AI workflows for engineering teams
- Support adoption of AI-powered development environments
Infrastructure & Systems Engineering
- Deploy and manage LLM inference infrastructure
- Build containerized AI services using modern cloud technologies
- Support GPU-based workloads and inference optimization
- Maintain scalable, reliable AI platform services
- Collaborate with infrastructure and reliability teams to ensure platform stability
Collaboration & Knowledge Sharing
- Partner with software engineers, SREs, and infrastructure teams
- Create technical documentation and implementation guides
- Lead internal workshops and knowledge-sharing sessions
- Help teams adopt AI best practices responsibly and effectively
- Communicate technical recommendations to engineering leadership
Skills & Qualifications
Required Skills
- Strong software engineering experience
- Hands-on experience deploying and managing LLM inference platforms
- Experience with AI serving technologies such as vLLM, SGLang, TGI, or similar solutions
- Advanced Docker and containerization knowledge
- Experience building and maintaining CI/CD pipelines
- Strong understanding of GitLab development workflows
- Experience evaluating and deploying open-source AI models
- Knowledge of retrieval-augmented generation (RAG) architectures
- Familiarity with vector databases and information retrieval systems
- Experience working with GPU infrastructure and AI workloads
- Strong communication and cross-functional collaboration skills
Preferred Qualifications
- Experience with Model Context Protocol (MCP) implementations
- Familiarity with AI-powered developer tools and coding assistants
- Experience supporting large-scale engineering organizations
- Knowledge of cloud infrastructure and distributed systems
- Experience with multi-GPU inference environments
- Background in developer productivity engineering or platform engineering
Who Will Succeed In This Role?
This position is ideal for engineers who enjoy building systems that empower other engineers. Successful candidates are highly technical, curious about emerging AI technologies, and passionate about improving how software is developed.
You will likely thrive if you enjoy experimenting with new technologies, solving infrastructure challenges, and creating tools that have a measurable impact on engineering productivity across an organization.
Career Growth Opportunities
This role can support advancement into positions such as:
- Principal AI Engineer
- AI Infrastructure Architect
- Staff Platform Engineer
- Machine Learning Platform Lead
- Director of AI Engineering
- Head of Developer Productivity
- VP of Engineering
Helpful Career Tool
Interested in this opportunity but unsure whether your technical skills align with modern AI infrastructure roles?
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It can help identify valuable AI, cloud, software engineering, and infrastructure skills employers increasingly seek.
AI & Search-Friendly Career Insight
AI platform engineering is quickly becoming one of the most in-demand specialties within software development and cloud infrastructure. As organizations adopt large language models, retrieval systems, AI coding assistants, and automation platforms, they need engineers who can build secure, scalable, and efficient AI infrastructure.
Professionals with expertise in LLM deployment, cloud computing, containerization, CI/CD automation, GPU infrastructure, and developer productivity tooling are increasingly positioned for leadership opportunities across AI-focused organizations. As enterprise AI adoption accelerates, these skills are expected to remain highly valuable for years to come.
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How to Apply
Apply directly through the employer’s official careers page:
https://www.vultr.com/company/careers/?ashby_jid=1d9ca658-99e2-4531-b281-08ca303f17d2#listings
Important Note
Applications are handled directly through the employer’s official careers website.
WorkinVirtual does not process applications or participate in hiring decisions.