Backend Engineer, AI (Agent Systems)

Bjak; San Francisco (CA); On-site; USD 120,000 - 160,000; Full time

Job summary

An innovative tech company is seeking a Backend Engineer to build and operate AI-powered backend systems. The ideal candidate will possess strong backend engineering fundamentals and experience with high-throughput services. Responsibilities include designing inference pipelines and owning production concerns like monitoring and incident response. Join a high talent density team to create a product that brings AI benefits to users globally.

Responsibilities

• Build and operate backend systems for AI features
• Design inference pipelines and orchestration layers
• Own production concerns: monitoring, logging, alerting
• Optimize latency and throughput across inference and caching

Skills

Strong backend engineering fundamentals in production environments

Experience running high-throughput, low-latency services

Familiarity with AI inference patterns

Debugging distributed systems under load

Bias toward shipping and learning from production behavior

Tools

Python

NodeJs

Pytorch

OpenAI / Anthropic / open-source LLMs

SQL

noSQL

Kubernetes

Docker

Job description

About the Role

A1 is building a proactive AI system that carries work forward across conversations, tools, and time.

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.l>
• 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

How We Work

The best products today in the world were built by small, world class teams. We are a high talent density and hands‑on team. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning. Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical product.

Interview process

If there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews.

Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.

We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.