Backend Engineer, AI (Agent Systems)
Bjak
You'll work on systems that actually matter early in your career. Bjak is building AI assistants that help everyday users complete real tasks faster. As a Backend Engineer on the AI team, you own the layer between models and users—where speed, reliability, and correctness directly affect millions of people. That's the kind of responsibility most grads don't get until year three or four.
Your job is to build and operate the inference and orchestration systems that power every AI interaction in the product. You'll design pipelines that handle multi-step reasoning, integrate external tools, and stay reliable even when model behavior isn't predictable. You're writing code that turns raw model capability into fast, stable APIs that mobile and desktop clients depend on. Latency, cost, and correctness are real constraints you'll optimize for.
This role fits you if you have solid fundamentals in backend systems, databases, or distributed computing. A computer science degree or equivalent portfolio helps. You don't need AI expertise—that's something you'll learn here. What matters is wanting to understand how systems fail and how to build things that don't.
Apply through CareerJumpShip to join Bjak's team in Germany. Remote work available.
About this role
About A1 There are over 5 billion users using basic applications today such email, notes, tasks that are not AI-native. Our mission is to build a proactive smart assistant for everyday users to bring intelligence to conversations, errands, organising and workflows, with minimal prompting. 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. Our objective is to help users complete tasks daily enjoyable with over ~90%* reduced time. 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 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. Originally posted on Himalayas
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