Senior Full-Stack Engineer (AI-Focused)

Role overview Build AI-powered capabilities for a SaaS product, owning work across user interfaces, backend services, APIs, and language model integrations. This senior individual contributor role combines hands-on delivery with input into technical direction, working closely with product, design, and engineering leadership.

Responsibilities - Develop and maintain full-stack product features, including embedded experiences and customer-facing AI tools. - Design production LLM workflows using techniques such as retrieval, tool calling, agent orchestration, and evaluation. - Extend integrations that let customers use product capabilities through AI tools and workflows. - Help shape architecture and roadmap, translating customer needs into useful technical solutions. - Measure and improve AI feature quality, reliability, latency, and operating cost. - Use AI coding assistants thoughtfully and help establish effective team workflows and safeguards.

Requirements - At least 6 years building and maintaining production SaaS applications as a full-stack engineer. - Strong TypeScript or JavaScript skills and experience creating responsive interfaces with a modern frontend framework. - Solid experience with Elixir and Python. - Practical experience shipping LLM-powered features, such as model API integrations, retrieval-augmented generation, tool use, or agents. - Ability to evaluate LLM output quality and reliability, and understand the effects of high-volume WebSocket traffic on system design. - Experience using AI coding assistants, with good judgment about review and technical safeguards. - Product sense, independent ownership, clear communication, and C1 or C2 English proficiency.

Nice to have - Experience building Model Context Protocol integrations, embedded JavaScript SDKs, or in-app product experiences. - Familiarity with LLM monitoring, tracing, and evaluation tools, or with product onboarding and adoption.

Benefits and work setup - Senior individual contributor position with substantial autonomy and direct collaboration with technical and product leadership. - Requires substantial overlap with US-based working hours; compensation is in USD and depends on experience. - Early priorities include shipping an AI feature, learning the existing product architecture, and improving AI delivery practices.