Sequen is a New York-based startup that provides real-time personalization and ranking infrastructure via its RankTune platform.
SENIOR STAFF SYSTEMS ENGINEER, RUST ENG. About the Company: Sequen AI is leading the charge for building frontier ranking models for search and recommendations. Sequen AI's technology specializes in designing end-user behavior for large consumer enterprises. We are a small, highly technical team at an early stage, focused on turning recent advances in AI into systems that are reliable, useful, and capable in practice. The problems we are working on are often ambiguous, with meaningful real-world constraints and impact. If you are interested in building blistering fast, memory-safe backend architectures and shaping how frontier AI models serve production traffic at enterprise scale, we would like to meet you. About the Role: We are looking for a Core Systems Engineer with a deep mastery of Rust to design, build, and optimize Sequen’s underlying model serving infrastructure and real-time performance engines. This role sits at the absolute core of our technical strategy. You will be responsible for ensuring our frontier ranking and recommendation APIs process petabyte-scale data and compute complex inference logic with ultra-low latency. You will replace high-overhead bottlenecks with elegant, production-grade Rust systems, building a reliable foundation that scales alongside our rapid enterprise customer growth. Responsibilities: - Optimize Real-Time Infrastructure: Write high-performance, memory-safe, and concurrent production code in Rust. Optimize model serving infrastructure to achieve ultra-low inference latency under heavy concurrent request loads. Build low-latency data ingestion systems, microservices, and network protocols to process real-time behavioral streams. - Develop Core Architectural Tooling: Design and maintain robust, high-throughput backend APIs and SDKs. Implement customized abstractions, caching layers, and memory management profiles to maximize hardware efficiency. Migrate data-heavy bottlenecks from higher-overhead languages into highly optimized Rust components. - Ensure Reliability and Scale: Own the end-to-end lifecycle of core backend infrastructure components. Debug complex distributed system deadlocks, race conditions, and production bottlenecks across cloud environments. Establish rigorous performance benchmarking, regression testing, and real-time system monitoring. - Collaborate on Product Evolution: Partner directly with Applied Scientists to translate recent neural network and ranking model breakthroughs into highly scalable runtime realities. Define best practices for building secure, scalable, and deterministic system architectures across our entire engineering organization. Qualifications: - 6 to 8+ years of experience in Software Engineering, Systems Programming, Infrastructure Engineering, or similar. - Strong professional experience writing and deploying production-grade Rust code in high-scale systems. - Deep understanding of Rust-specific primitives, including ownership, lifetimes, concurrency models, and asynchronous runtimes like Tokio. - Experience building robust backend systems, custom APIs, and event-driven architectures. - Experience debugging, profiling, and operating high-throughput production systems under strict real-world constraints. - Comfort with ambiguity, a strong sense of technical ownership, and an ability to balance engineering speed with quality. Preferred Skills: - Experience working with cloud platforms like AWS, GCP, or Azure and container orchestration tools like Docker and Kubernetes. - Experience implementing machine learning model inference optimizations, vector search databases, or large-scale data pipelines. - Background in early-stage startups or fast-moving, high-growth technical environments. Pay range and compensation package: At this stage, the efficiency and speed of our core infrastructure directly dictate how our product performs for global-scale consumer enterprises. You will have a blank canvas to architect core systems, work with bleeding-edge AI workflows, and fundamentally define the technical scalability of the company.