(Senior) AI Engineer

A high-impact and technically deep (Senior) AI Engineer role has become available in a fast-growing AI product company, offering the opportunity to own the core infrastructure and systems that power a proactive, long-horizon AI assistant used by millions.

Key responsibilities:

• Own the end-to-end AI backend and orchestration layer: inference services, agent runtime, tool integrations, and APIs used across mobile and desktop clients.
• Design and operate low-latency, high-throughput services that turn model capabilities into stable, observable production systems.
• Build and maintain agent workflows that handle planning, multi-step tool use, failure detection, recovery, and consistent user outcomes.
• Develop and evolve the ML platform: model serving infrastructure, deployment pipelines, evaluation/benchmarking systems, and experiment tooling for AI engineers and researchers.
• Implement robust observability, monitoring, tracing, and alerting for AI workloads; lead incident response and continuous reliability improvements.
• Optimize latency, throughput, cost, and reliability across inference, caching, batching, streaming, and GPU utilization.
• Define clear service boundaries and abstractions between models, backend services, and product layers to enable rapid iteration.
• Collaborate closely with ML model owners, product, and frontend engineers to ensure AI features are performant, dependable, and aligned with user needs.

Profile:

• Master’s or Bachelor’s degree in computer science, engineering, or a related technical field (or equivalent practical experience).
• 5+ years of experience building and operating production backend systems, distributed services, or ML/AI infrastructure in a high-scale environment.
• Tech stack: Strong expertise in Python and Node.js for backend services; experience with PyTorch/JAX, LLM serving (vLLM, SGLang, TensorRT-LLM or similar), Kubernetes/Docker, cloud infrastructure, SQL/NoSQL and vector databases, and production observability stacks. Frontend experience (e.g., Next.js) is a plus.
• Strong software engineering fundamentals: clean, maintainable code; system design; API architecture; debugging under load.
• Hands-on experience with AI/LLM systems: inference patterns, RAG, agent workflows, tool integration, streaming, and partial results.
• Proven track record designing and running low-latency, high-throughput services (e.g., inference servers, real-time APIs, event-driven systems).
• Experience with ML platform components: model serving, deployment pipelines, evaluation frameworks, data/ML pipelines, and observability.
• Structured, data-driven, and comfortable working with ambiguity, evolving requirements, and complex distributed systems.
• Strong ownership mindset: able to take ambiguous problems, design practical solutions, and ship iteratively based on real usage signals.
• Excellent communication skills and ability to collaborate across ML, product, and engineering teams in a fast-paced environment.
• Full professional proficiency in English.

This is a rare opportunity to shape the technical foundation of a next-generation AI assistant, directly influencing reliability, performance, and user experience at scale. Apply if you believe this is your next challenge.