AI / ML Platform Engineer

Vertiv Group•Westerville, OH

2d•Onsite

About The Position

Vertiv is seeking a technically skilled and innovative AI / ML Platform Engineer to serve as the hands-on engineering lead for enterprise AI platform capabilities within Vertiv’s Digital organization. This individual contributor role is responsible for supporting, administering, and extending Vertiv’s production AI platforms — including Writer AI and Compass AI — while owning the development of prompt engineering standards, and AI governance frameworks that ensure responsible, compliant, and high-quality AI outputs across the enterprise. The AI / ML Platform Engineer will operate within the Digital organization and play a central role in advancing Vertiv’s Operational Excellence and Customer Focus & Innovation strategic priorities by enabling scalable, governed, and production-grade generative AI capabilities that deliver measurable business value. As an individual contributor in a lead capacity, this role extends beyond hands-on platform engineering to encompass the full lifecycle of LLM -based application delivery — from model evaluation and prompt optimization to LLMOps monitoring and cross-functional AI enablement. The AI / ML Platform Engineer will partner closely with technology and business stakeholders to define AI usage policies, evaluate emerging GenAI technologies, and ensure that all AI solutions are secure, observable, and aligned to Vertiv’s enterprise architecture and data governance standards. This position is based onsite at Vertiv’s Westerville, OH headquarters, with occasional domestic and international travel as needed.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Science, or a related field; equivalent practical experience considered.
5+ years of professional experience in software engineering, AI/ML engineering, or a related technical discipline.
3+ years of hands-on experience building and deploying GenAI / LLM-based applications or platforms in a production enterprise environment.
Demonstrated experience with prompt engineering , RAG pipeline development, and LLM API integration in real-world production systems.
Experience with enterprise AI platform administration (e.g., Writer AI , Compass AI , or equivalent SaaS AI platforms) is strongly preferred.
Proficiency in Python for AI/ML engineering, data processing, and pipeline development.
Hands-on experience with RAG architectures , vector search technologies (e.g., Pinecone, Weaviate, pgvector, OpenSearch), and embedding models.
Experience with LLM APIs and frameworks (e.g., OpenAI, Anthropic, LangChain, LlamaIndex, or equivalent) for building production AI applications.
Familiarity with AWS AI/ML services (SageMaker, Bedrock, or equivalent) and cloud-native deployment patterns.
Experience with CI/CD pipelines and DevOps tooling (Gitlab, Jenkins, GitHub Actions, Azure DevOps, or equivalent) for AI application delivery.
Working knowledge of prompt engineering best practices, prompt versioning, and LLMOps tooling (e.g., MLflow, LangSmith, Weights & Biases, or equivalent).

Nice To Haves

AWS AI/ML certifications (AWS Certified Machine Learning – Specialty, or AWS Certified AI Practitioner).
Direct hands-on experience with Writer AI and/or Compass AI platform administration and integration.
Familiarity with enterprise LLMOps tooling, AI observability platforms, and model evaluation frameworks.
Experience with Snowflake or other cloud data platforms for AI/ML data pipelines and feature engineering.
Exposure to AI governance frameworks, responsible AI principles, and enterprise AI policy development.
Experience working in Agile/Scrum delivery environments with cross-functional digital product teams.

Responsibilities

Serve as the primary technical owner for Vertiv’s Writer AI and Compass AI platform instances, managing configuration, tenant administration, integrations, user access controls, and platform health to ensure reliable, production-grade availability across the enterprise.
Design, develop, test, and continuously refine prompts and prompt templates for LLM-powered applications, establishing enterprise-wide prompt engineering standards, libraries, and versioning practices that maximize model accuracy, consistency, and safety.
Architect and implement end-to-end Retrieval-Augmented Generation (RAG) pipelines — including document ingestion, chunking strategies, embedding generation, and vector search integration — to ground LLM outputs in authoritative Vertiv knowledge sources and reduce hallucination risk.
Define and enforce AI usage policies, content safety guardrails, data handling standards, and compliance controls across all GenAI platforms and applications, partnering with Legal, Compliance, IT Security, and NPDi teams to ensure responsible AI practices aligned to Vertiv’s risk framework.
Implement and maintain LLMOps tooling for production AI systems, including prompt performance monitoring, output quality tracking, cost management, latency observability, and model drift detection, ensuring that AI applications remain performant, reliable, and cost-effective at scale.
Partner with technology and business stakeholders to translate requirements into technical AI solutions, provide platform consulting for new GenAI use cases, and serve as a technical subject matter expert on LLM capabilities, limitations, and integration patterns.
Develop systematic evaluation frameworks and benchmarks for assessing LLM output quality, prompt effectiveness, RAG retrieval accuracy, and model behavior — enabling data-driven decisions on model selection, prompt iteration, and platform evolution.
Continuously monitor advancements in generative AI, large language models, agentic AI frameworks, and enterprise AI platforms; evaluate emerging tools and techniques for applicability to Vertiv’s AI roadmap and provide actionable recommendations to Digital leadership.