Senior AI Platform Architect & Infrastructure Engineer

Framework Ventures; Vienna (VA); On-site; USD 150,000 - 210,000; Full time

Job summary

Framework Ventures is seeking a Senior AI Engineer to design and evolve large-scale AI infrastructure that powers mission-critical ML workloads across business lines. You will build platforms enabling teams to develop, train, deploy, and operate AI models reliably at scale.

The role sits at the intersection of systems engineering and applied AI, shaping long-term platform strategy while tackling architecture, performance, and reliability challenges across compute, data, and ML systems.

Qualifications

• Bachelor’s Degree in CS, IT, Engineering or equivalent with 5+ years of relevant industry experience.
• Experience in AI Agent / RAG engineering solutions.
• Experience in Microservices/API development with Java/SpringBoot/SpringCloud/Python/Langchain.
• Knowledge of multi‑threading and distributed architecture.
• Familiarity with Kafka and other messaging frameworks.

Responsibilities

• Build large-scale AI infrastructure for training, fine-tuning, and deployment of AI models.
• Develop scalable systems across compute, storage, networking, and orchestration layers.
• Drive performance, reliability, and cost optimization for AI workloads at scale.
• Partner with the AI Science team and relevant business units to translate requirements into platform capabilities.
• Advise on best practices for AI platform development including scalability, reliability, observability, security, and operations.

Skills

AI/ML infrastructure

Distributed systems

Multi-threading

AI Agent / RAG experience

Education

Bachelor's degree in CS/IT/Engineering

Tools

Java

SpringBoot

SpringCloud

Python

Langchain

Kafka

Job description

Framework Ventures is seeking a Senior AI Engineer to design and evolve large-scale AI infrastructure that powers mission-critical ML workloads across business lines. You will build platforms enabling teams to develop, train, deploy, and operate AI models reliably at scale.

The role sits at the intersection of systems engineering and applied AI, shaping long-term platform strategy while tackling architecture, performance, and reliability challenges across compute, data, and ML systems.