Architect – Platform Engineering

Quantiphi

AI Platform/AIOps Architect developing ML solutions to solve complex business problems at Quantiphi. Leading MLOps strategy and collaborating with cross-functional teams on AI and cloud technologies.

Posted 5/21/2026full-timeRemote • Illinois • 🇺🇸 United StatesSeniorLeadWebsite

Tech Stack

Tools & technologies

CloudGoogle Cloud PlatformPythonSparkSQL

About the role

Key responsibilities & impact

Architect and implement the MLOps strategy for the program
Design and own enterprise-grade ML/LLM pipelines
Build container-oriented ML platforms (GKE-first)
Implement hybrid MLOps + LLMOps workflows
Serve as a technical authority across multiple internal and customer projects
Enable observability, monitoring, drift detection, lineage tracking, and auditability across ML/LLM systems
Collaborate with cross-functional teams to deliver production-ready ML solutions
Ensure all solutions adhere to security, governance, and compliance expectations
Conduct architecture reviews, troubleshoot complex ML system issues, and guide teams through implementation
Mentor engineers and provide guidance on modern MLOps tools

Requirements

What you’ll need

10+ years working in ML/AI platform engineering or AI/MLOps roles with strong architecture exposure
Strong expertise in the Google Cloud (GCP) native AI/ML stack
Hands-on experience with MLOps toolset
Deep understanding of model lifecycle management
Experience implementing or supporting LLMOps pipelines
Strong experience with Google Cloud's Vertex AI platform
Experience implementing ML CI/CD pipelines
Strong SQL and data transformation experience using Snowflake, Databricks, Spark
Understanding of lineage tracking
Strong foundation in Python and cloud-native development patterns
Solid understanding of security best practices, Cloud IAM, secrets management, and artifact governance

Benefits

Comp & perks

Be part of the fastest-growing AI-first digital transformation and engineering company in the world
Be a leader of an energetic team of highly dynamic and talented individuals
Exposure to working with fortune 500 companies and innovative market disruptors
Exposure to the latest technologies related to artificial intelligence and machine learning
Opportunities to learn, grow and interact with colleagues from varied experience and backgrounds around the globe

ATS Keywords

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Hard Skills & Tools

MLOpsLLMOpsML pipelinesmodel lifecycle managementML CI/CD pipelinesPythonSQLdata transformationcloud-native development patternsarchitecture reviews

Soft Skills

mentoringcollaborationtroubleshootingguidancetechnical authority