Senior Software Engineer - AI

Role overview A senior AI engineer role focused on designing and shipping AI-powered features end-to-end inside a customer-feedback product line. This is a hands-on individual contributor position with real technical ownership, expected to make architectural calls within its domain rather than execute a fixed spec. The engineer will be one of two shaping how intelligent capabilities—automated setup, contextual analysis, self-generating reporting—move reliably into production.

Responsibilities - Design, build, and ship AI-powered features across the product, from prototype through production launch - Work directly with LLMs, embeddings, and adjacent tooling to address concrete product problems - Own technical decisions: architecture, model selection, integration approach, and quality/cost/latency tradeoffs - Build across the full stack as needed, ensuring shipped features are tested, monitored, and maintainable - Establish reusable patterns for AI feature development and surface risks around reliability, cost, and edge cases early - Partner with engineering leadership on planning and sequencing, and with product on requirements (including pushing back with technical reality)

Requirements - 7+ years of software engineering experience, including AI features shipped to production with full lifecycle ownership - Strong fullstack fundamentals, comfortable across frontend, backend, and infrastructure - Practical experience with LLM APIs, prompt engineering, RAG, or similar techniques in live systems - Evaluation mindset: defining success metrics, designing experiments, running offline and online evaluations - Data competence: solid SQL, basic schema design, simple pipelines, hands-on analysis - Production readiness: Docker, CI/CD awareness, logging/monitoring basics, versioning of prompts, models, and datasets

Nice to have - LLM platform breadth across multiple providers, vector databases, and frameworks such as LangChain, plus comfort with fine-tuning when warranted - Compliance or security experience, especially as the product moves upmarket - A track record of proactive problem framing on ambiguous, technically complex work

Benefits and work setup - Fully remote with flexible working hours - High-trust team culture with significant autonomy and minimal bureaucracy - Flexible time off to recharge - Small, collaborative team that supports each other - Access to a wider network of SaaS professionals for knowledge sharing and learning