Senior AI Platform Architect for Production-grade ML Infra

Evolution USA; United States; On-site; USD 180,000 - 240,000; Full time

Job summary

Evolution USA is seeking a Lead Software Platform Engineer to own the architecture, scalability, and operational excellence of a next-generation AI and ML platform. You will lead the design of a cloud-native system that safely deploys LLMs, agents, and AI workloads in production for external users.

You will influence technical direction, standards, and engineering practices while mentoring other engineers across the organization.

Qualifications

• 10+ years of software engineering and cloud infra experience.
• Proven ability to design and scale distributed, cloud-native systems in production.
• Experience as a technical lead, architect, or principal engineer responsible for major architectural decisions.
• Hands-on experience building and operating AI/ML infrastructure at scale.
• Strong knowledge of modern LLM architectures and deployment patterns (RAG, embeddings, prompt management).
• Backend focus with Python and TypeScript, API development.

Responsibilities

• Own architecture and roadmap for a cloud-native AI and ML platform.
• Design scalable infra for model deployment, lifecycle, and multi-model serving.
• Build reliable real-time and batch inference systems.
• Develop frameworks for LLM apps, retrieval systems, and agent architectures in production.
• Define platform security, governance, tenant isolation, and data protection standards.
• Lead design reviews and mentor engineers on architecture and scalability.
• Drive observability, monitoring, and incident response for production workloads.

Skills

Python

TypeScript

Cloud-native

Distributed systems

LLM deployment

AI infra

CI/CD

Security/compliance

Observability

Leadership

Tools

AWS

Kubernetes

Terraform

Docker

CI/CD pipelines

Job description

Evolution USA is seeking a Lead Software Platform Engineer to own the architecture, scalability, and operational excellence of a next-generation AI and ML platform. You will lead the design of a cloud-native system that safely deploys LLMs, agents, and AI workloads in production for external users.

You will influence technical direction, standards, and engineering practices while mentoring other engineers across the organization.