ML Platform Architect – Agentic AI & MLOps

Quantiphi; Dallas (TX); Hybrid; USD 180,000 - 240,000; Full time

Job summary

Quantiphi seeks an experienced Associate Architect – Machine Learning Engineering (MLE) to design and deliver scalable AI/ML platforms and agentic AI solutions for enterprise applications. You will provide technical leadership in building production-grade ML systems and evolving Python SDK frameworks.

This role requires deep expertise in Python, FastAPI, MLOps, and distributed AI systems, with the ability to mentor engineers and drive architectural excellence across multiple initiatives.

Qualifications

• Expert-level proficiency in Python for enterprise-grade ML apps.
• Strong understanding of API design, OOP, and software engineering.
• Experience designing Agentic AI workflows and multi-agent systems.
• Experience building production-ready AI apps using modern agentic frameworks.
• Knowledge of LLM orchestration and autonomous agents is a plus.

Responsibilities

• Architect and evolve Python SDK frameworks for AI platforms.
• Design scalable Agentic AI architectures and multi-agent systems.
• Lead design and implementation of reusable AI platform components for performance and security.
• Build and optimize high-performance RESTful APIs with FastAPI for AI services.
• Define standards, guidelines, and best practices for ML platforms and SDKs.
• Design CI/CD pipelines using Jenkins and GitLab Runners to enable deployment.

Skills

Python

FastAPI

MLOps

Distributed AI

SDK development

Mentoring

Tools

Docker

Kubernetes

Terraform

Job description

Quantiphi seeks an experienced Associate Architect – Machine Learning Engineering (MLE) to design and deliver scalable AI/ML platforms and agentic AI solutions for enterprise applications. You will provide technical leadership in building production-grade ML systems and evolving Python SDK frameworks.

This role requires deep expertise in Python, FastAPI, MLOps, and distributed AI systems, with the ability to mentor engineers and drive architectural excellence across multiple initiatives.