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Backend Engineer, AI (Agent Systems)

Bjakcareer · United States

remoteunknownPosted Sep 25, 2026PythonNodeJsPyTorchOpenAIAnthropicLLMsKubernetesDocker

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About this role

## About ACTAI ACTAI is building proactive applications for the 5B+ users who rely on basic tools (email, notes, tasks, calendars) that aren’t AI-native. Our mission is to bring intelligence to conversations, errands, organizing, and workflows—**with minimal to no prompting**. We focus on: - **High reliability** for long-running workflows - **Persistent context** - **Real-world task completion** - Reducing **hallucinations** through product design ## Role: Backend Engineer, AI (Agent Systems) You’ll 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 affect 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** via 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** - Stable, clear APIs that integrate smoothly with frontend and ML systems - Incidents are detected, diagnosed, and resolved quickly to minimize user impact - Continuous improvements based on real usage ## Tech Stack - Python, Node.js - PyTorch - OpenAI / Anthropic / open-source LLMs - SQL & NoSQL - Kubernetes, Docker ## How We Work Small, world-class teams with high talent density. Decisions are collective and execution is fast—balancing shipping quality work with learning. ## Interview Process - If there’s a fit, you’ll be scheduled for **3 interviews** (no more than **4**) - Virtual meetings and/or onsite - Prompt decisions with transparency and efficiency ## What This Is Not just a job—an invitation to help bring AI with practical benefits to **billions globally**.

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