Do you excel at solving complex backend challenges like streaming responses, intelligent batching, low-latency caching, and API optimization under heavy load?
Are you looking for a high-impact backend role where system reliability, cost efficiency, and ultra-low latency directly drive the product experience?
Great, then please read on as we have a role for you.
Our clients mission is to fundamentally change the productivity landscape around email, calendars and note taking by developing proactive, AI-native applications designed for the general public. We are bringing seamless intelligence to workflows, scheduling, and daily errands, all without requiring users to master complex prompting.
As a Backend Engineer specializing in AI infrastructure, you will own the inference and orchestration layer that powers intelligent features across all client platforms. Operating at the intersection of machine learning models and end-user applications, you will build and run high-scale production systems where latency, reliability, correctness, and cost efficiency directly drive the user experience.
Key Responsibilities
- Build and operate scalable backend systems that serve AI-powered features in production.
- Design high-performance inference pipelines, orchestration workflows, and clear service boundaries around ML models.
- Own system health and observability, including performance monitoring, structured logging, alerting, and incident response.
- Optimize system latency and throughput through intelligent caching strategies, request batching, and response streaming.
- Collaborate with client and machine learning engineers to deliver stable, high-efficiency APIs for mobile and desktop applications.
To be a good fit for the Backend Engineer role, you will have:
- Proven background in core backend software engineering within production environments. ( Python, Node.js)
- Infrastructure Experience with Docker, Kubernetes
- Practical experience building and maintaining high-throughput, low-latency distributed microservices.
- Solid understanding of modern AI inference patterns, including LLMs, vector embeddings, and multimodal architectures.
- Hands-on experience debugging and profiling complex distributed systems operating under heavy load.
- Familiarity with commercial AI APIs (e.g., OpenAI, Anthropic) as well as self-hosted open-source models.
- Production-focused mindset with a strong bias toward shipping, observing live system behavior, and iterating quickly.
Reasons to join:
- Small founding team, building a greenfield AI email product from scratch.
- High‑caliber engineers from top tech companies; very high technical bar.
- Fully remote, global team, strong ownership, and visible impact.
- Very strong reward culture (including significant equity and high comp flexibility
Sounds interesting? Send us your CV by applying to this page
