AI Platform Engineer: MLOps, LLM Tooling & Data Pipelines

Globality; Palo Alto (CA); On-site; USD 140,000 - 200,000; Full time

Benefits offered by this job

Premium Health Benefits

Distributed Team Building

Learning & Development

Award Winning Culture

Job summary

Globality is seeking an AI Platform Engineer to design and implement scalable AI platforms using Python and MLOps tooling. You will interface with large language models through prompting frameworks, LangGraph, and orchestration services, enabling teams to deploy and iterate on intelligent applications.

The role emphasizes data pipelines, model monitoring, and rigorous testing, with a focus on secure, ethical AI usage and cross-team collaboration across engineering and product groups.

Qualifications

• 4+ years of experience building production-grade AI/ML platforms.
• Experience with large-scale data pipelines (e.g., Apache Spark, Kafka).
• Certifications in cloud platforms, ML engineering, or specific AI tooling.
• Strong software engineering skills in Python and familiarity with Java/Go and OOP/data structures.
• Awareness of AI ethics, biases, fairness, and data privacy protocols.
• Excellent communication and collaboration across engineering and product teams.

Responsibilities

• Design and implement scalable AI platforms using Python and MLOps tooling.
• Interface with LLMs via prompting frameworks, agentic workflows, and orchestration services.

Skills

MLOps

Python

Cloud deployment

Data pipelines

Education

Bachelor’s or Master’s in Computer Science, Engineering, or related field

Tools

Docker

Kubernetes

Apache Spark

Kafka

LangGraph

Job description

Globality is seeking an AI Platform Engineer to design and implement scalable AI platforms using Python and MLOps tooling. You will interface with large language models through prompting frameworks, LangGraph, and orchestration services, enabling teams to deploy and iterate on intelligent applications.

The role emphasizes data pipelines, model monitoring, and rigorous testing, with a focus on secure, ethical AI usage and cross-team collaboration across engineering and product groups.