Software Engineer, Platform - Cleveland, OH, USA

🏢 Summary: Backend Engineer role focused on building and operating the AI inference and orchestration systems behind a production AI assistant. The position emphasizes low-latency, high-throughput APIs, distributed-system reliability, observability and performance optimization for mobile, desktop and machine-learning integrations. Remote-first collaboration is available for a candidate working from Poland, with base salary and equity assessed individually. 🗂️ Requirements: Production backend engineering experience, High-throughput, low-latency service experience, AI inference familiarity: LLMs, embeddings, multimodal models, Distributed-systems debugging under load, Production observability and incident-management knowledge, Performance-optimization expertise, Independent delivery in ambiguous environments, Working from Poland, Working-hours overlap with immediate team 📃 Skills: Python, Node.js, PyTorch, OpenAI, Anthropic, LLMs, Embeddings, SQL, NoSQL, Kubernetes, Docker, APIs, Caching, Batching, Streaming, Logging, Alerting 🏢 Description: About the product Our client is developing an AI-native assistant designed to support everyday communication, organization, errands and complex workflows with minimal user input. The product must reliably manage long-running processes, retain context, interact with external tools and complete real-world tasks despite the non-deterministic nature of modern AI models. The company’s objective is to make everyday activities significantly faster and easier for users. About the role As a Backend Engineer specializing in AI systems, you will own the inference and orchestration layer behind the product’s AI interactions. Your work will sit between models and end users, where latency, correctness, reliability and operating costs directly affect the product experience. You will build and operate production systems that transform model capabilities into fast, stable and observable APIs used by mobile and desktop applications. What you will do Build and operate backend systems serving AI-powered functionality in production. Design inference pipelines, orchestration layers and service boundaries around Machine Learning models. Take ownership of production monitoring, logging, alerting and incident response. Optimize latency and throughput across inference, caching, batching and streaming. Build reliable APIs supporting integration with mobile, frontend and Machine Learning systems. Diagnose distributed-system issues under production load. Continuously improve system performance and reliability using real-world production signals. What we are looking for Strong backend engineering fundamentals supported by experience with production systems. Experience building or operating high-throughput, low-latency services. Familiarity with AI inference patterns, including LLMs, embeddings and multimodal models. Confidence debugging distributed systems under load. Understanding of production observability, incident management and performance optimization. A delivery-oriented mindset focused on shipping, observing production behavior and improving through iteration. Ability to work independently and make pragmatic engineering decisions in an ambiguous environment. What success looks like Backend systems reliably handle production AI traffic at scale with low latency and high throughput. APIs remain stable, clear and easy to integrate with frontend, mobile and Machine Learning systems. Production incidents are detected quickly, diagnosed effectively and resolved with minimal impact on users. System performance and reliability improve continuously based on real-world usage and production data. Technology stack Python Node.js PyTorch OpenAI, Anthropic and open-source LLMs SQL and NoSQL databases Kubernetes Docker Compensation and employment The position is offered under an employment contract. The company does not publish a fixed external salary range. Compensation is assessed individually based on: professional experience and technical capability, scope of responsibility, location and relevant market benchmarks, expected impact on the product and organization. Candidates may share their expected compensation at the beginning of the recruitment process. The compensation package consists of a base salary and equity, with flexibility for exceptional candidates. A company laptop will be provided where required for the role. Remote work and global collaboration The company operates as a remote-first, globally distributed organization. There is no fixed company-wide working schedule and no requirement to follow one specific time zone. Team members are expected to maintain sufficient working-hours overlap with their immediate colleagues to collaborate effectively. The successful candidate will work from Poland and collaborate with backend, Machine Learning, mobile and product specialists located across different regions. Poland-based employees join existing global teams rather than a separate local team. The exact reporting line and hiring manager will be confirmed during the recruitment process. How the team works The company believes that outstanding products are built by small, highly capable and hands-on teams. Decisions are made collaboratively, while individuals are expected to take ownership, bring structure to ambiguous problems and execute independently. The team moves quickly while balancing production quality, experimentation and continuous learning from real user behavior. There is no fixed hiring quota for this position. The company is focused on identifying engineers who meet its technical and ownership standards rather than filling a predetermined number of seats. Recruitment process The standard recruitment process consists of up to four stages: Technical assessment, where relevant to the candidate’s background. HR interview. One or more technical interviews. Founder or leadership interview. Particularly strong candidates may be fast-tracked directly to the technical interview stage based on their experience and previous work. Applications are evaluated by members of the technical team. Interviews may be conducted virtually and, where relevant, onsite. The exact format and interviewers may vary. The company aims to make decisions efficiently and provide candidates with a prompt outcome.