Backend Engineer, AI (Agent Systems)

European Recruitment BV; United States; On-site; USD 120,000 - 160,000; Full time

Job summary

European Recruitment BV is seeking a Backend Engineer, AI, to own the inference and orchestration layer powering AI interactions in the product. You will build and operate production APIs used across mobile and desktop clients, balancing latency, correctness, reliability and cost.

You will design and operate high-throughput backend systems, pipelines and service boundaries around models, while monitoring, logging and incident response to keep production AI traffic fast and reliable.

Qualifications

• Strong backend engineering fundamentals in production environments.
• Experience designing low-latency, high-throughput services.
• Familiarity with AI inference patterns (LLMs, embeddings, multimodal).
• Comfortable debugging distributed systems under load.

Responsibilities

• Build and operate backend systems that serve AI-powered features in production.
• Design inference pipelines, orchestration layers, and service boundaries around models.
• Own production concerns: monitoring, logging, alerting, and incident response.
• Optimize latency and throughput across inference, caching, batching, and streaming.

Skills

Backend engineering

Low-latency design

Tools

Python

NodeJs

Pytorch

OpenAI / Anthropic / open-source LLMs

SQL

NoSQL

Kubernetes

Docker

Job description

Role

As a Backend Engineer, AI, you own the inference and orchestration layer that powers every AI interaction in the product. Your work sits between models and users, where latency, correctness, reliability, and cost directly impact real-world experience.

You will build and operate production systems that turn model capability into fast, stable, observable APIs used across mobile and desktop clients.

Focus

• Build and operate backend systems that serve AI-powered features in production.
• Design inference pipelines, orchestration layers, and service boundaries around models.
• Own production concerns: monitoring, logging, alerting, and incident response.
• Optimize latency and throughput across inference, caching, batching, and streaming.

Ideal Experiences

• Strong backend engineering fundamentals in production environments.
• Experience running high-throughput, low-latency services.
• Familiarity with AI inference patterns (LLMs, embeddings, multimodal).
• Comfortable debugging distributed systems under load.
• Bias toward shipping and learning from production behavior.

Outcomes

• Backend systems run reliably at scale, handling production AI traffic with low latency and high throughput.
• APIs are stable, clear, and support seamless integration with frontend and ML systems.
• Production incidents are quickly detected, diagnosed, and resolved, minimizing user impact.
• Iterative improvements based on real usage continuously increase system performance and reliability.

Tech Stack

• Python
• NodeJs
• Pytorch
• OpenAI / Anthropic / open-source LLMs
• SQL & noSQL
• Kubernetes
• Docker