Project description
About the Project: Over 5 billion people use traditional, non-AI-native apps daily for email, notes, tasks, and calendars. Our client's mission is to build proactive applications for everyday users who aren't accustomed to complex prompting. Their platform aims to bring intelligence to conversations, errands, organization, and workflows effortlessly. By focusing on persistent context, real-world task execution, and high reliability for long-running workflows, their app minimizes AI hallucinations—with the ultimate objective of organizing users' lives so they can focus on what truly matters.
Technical requirements
- Python
- NodeJs
- Pytorch
- OpenAI / Anthropic / open-source LLMs
- SQL & noSQL
- Kubernetes
- Docker
Responsibilities
As a Backend Engineer, 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.
- 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.
- Ensure backend systems run reliably at scale, handling production AI traffic with low latency and high throughput.
Must have
- 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.
Recruitment process
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. Please note that due to the volume of applications, we will only contact selected candidates.
Got questions?
To learn more details about this job contact Joanna at [email protected]