Backend Engineer, AI (Agent Systems)

BJAK; Greater London; On-site; GBP 50,000 - 70,000; Full time

Job summary

BJAK is looking for a Backend Engineer (AI) to build and maintain backend systems for their innovative AI chat application. Your role will involve designing inference pipelines and ensuring the reliability of production systems. The ideal candidate should have strong backend engineering skills, experience in high-throughput services, and familiarity with AI inference patterns. The position offers the chance to be part of a hands-on team that values rapid decision-making and quality work.

Qualifications

• Strong backend engineering fundamentals in production environments.
• Experience running high-throughput, low-latency services.
• Familiarity with AI inference patterns (LLMs, embeddings, multimodal).

Responsibilities

• Build and operate backend systems that serve AI-powered features.
• Design inference pipelines, orchestration layers, and service boundaries.
• Own production concerns: monitoring, logging, and incident response.

Skills

Backend engineering fundamentals

High-throughput services

AI inference patterns

Debugging distributed systems

Production behavior analysis

Tools

Python

NodeJs

Pytorch

SQL

noSQL

Kubernetes

Docker

Job description

About the Role

A1 is building a proactive AI chat app for everyday users to bring intelligence to conversations, errands, organising and workflows. Unlike traditional chat-based applications, our product focuses on achieving high reliability for long-running workflows, persistent context, and real‑world task completion. The system must handle multi‑step reasoning, interact with external tools, and remain reliable despite non‑deterministic model behavior.

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

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.