COMPANY A1
AI
BackendEngineer,AI(AgentSystems)
Neural analysis suggests this role is
optimal for Mid candidates.
“Backend Engineer, AI (Agent Systems) at COMPANY A1. Skills: Backend Engineering, AI Inference, Orchestration Layer. Build and operate backend systems. Design inference pipelines”
What You'll Achieve.
Backend systems run reliably at scale; handling production AI traffic; low latency; high throughput; APIs are stable; APIs are clear; support seamless integration; Production incidents are quickly detected; Production incidents are diagnosed; Production incidents are resolved; minimizing user impact; Iterative improvements; increase system performance; increase system reliability
Industry & Context.
multi-step reasoning; debugging distributed systems
What They're Looking For.
Must Have
backend engineering fundamentals in production environments, running high-throughput, low-latency services, debugging distributed systems under load, Bias toward shipping and learning from production behavior
Nice to Have
AI inference patterns (LLMs, embeddings, multimodal)
What You'll Do.
Build and operate backend systems
Design inference pipelines
Design orchestration layers
Design service boundaries
Own production concerns
How You'll Work.
Team & Collaboration
make decisions collectively; work with product team
Full Job Description
COMPANY A1 is building a proactive AI smart assistant for everyday users to bring intelligence to conversations, errands, organising and workflows. 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. 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 -
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