Backend Engineer AI (Agent Systems).
VASERJOB
San Francisco, CA, US
Onsite
2026-06-25
Announced salary
$120k–$290k
Low
$119K
Median
$166K
High
$214K
Market in San Francisco · BLS OEWS 2025
Job description
**Overview**
Join our innovative team as a Backend Engineer specializing in AI and Agent Systems, where you'll play a pivotal role in designing, developing, and optimizing backend solutions that power intelligent agents and AI\-driven applications. This position offers an exciting opportunity to work at the forefront of technology, leveraging cutting\-edge tools and frameworks to create scalable, reliable, and efficient systems. Your expertise will directly impact the development of next\-generation AI agents that enhance user experiences across diverse platforms.
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