Senior AI Engineer

Usersnap is building AI-driven capabilities into the core of the product, from automated setup to intelligent surveys, contextual analysis, and reporting that generates itself based on connectors. We're looking for a hands-on Senior AI engineer who designs and ships AI-powered features end-to-end, working closely with fellow engineers to bring these capabilities to production quality.

This is an IC role with real technical ownership. You'll be trusted to make architecture decisions within your area, not just execute someone else's spec, and to spot problems and propose solutions before anyone has to ask. AI capability is becoming core to Usersnap's product and go-to-market, and you'll be one of two engineers making sure it actually ships reliably and at production quality.

Your immediate impact in the first 3-6 months will be:

• You'll have shipped at least one AI-powered feature to production, end-to-end, from prototype through launch
• You'll have established technical patterns for AI feature development that the rest of the team can reuse
• You'll have built a strong working rhythm with the rest of the Engineering Team and Product
• You'll be recognized as a reliable owner of ambiguous, technically complex work

Your responsibilities

• Design, build, and ship AI-powered features across the product, from prototyping through production quality
• Work hands-on with LLMs, embeddings, and related AI tooling to solve real product problems, not just experiment with them
• Own technical decisions for your features: architecture, model selection and integration approach, and the tradeoffs between quality, cost, and latency
• Build across the stack as needed. This is a fullstack AI dev role, not siloed to backend or frontend, and every feature you ship should be tested, monitored, and maintainable
• Help establish good practices for AI feature development as our AI surface area grows, and flag technical risks early, especially around AI reliability, cost, and edge-case behavior
• Partner closely with the Senior Engineering Manager on technical planning and sequencing, with Product on requirements (pushing back with technical reality when needed), and with the rest of the engineering team on shared architecture and standards

What You bring to the table

• 7+ years of software engineering experience, you've shipped AI features to production and owned the lifecycle from problem framing to post-launch iteration, not just prototypes or AI-assisted coding
• Strong fullstack fundamentals; comfortable across frontend, backend, and infrastructure as needed
• Practical experience with LLM APIs, prompt engineering, RAG, or similar techniques in live systems, with good judgment about when AI is the right tool and when it isn't
• Evaluation mindset, you define success metrics, design experiments, run offline and online evaluations, and make decisions from the results
• Data competence, solid SQL, basic schema design, the ability to build simple pipelines, and a willingness to get your hands dirty with data through analysis and exploration
• Production readiness, Docker fluency, CI/CD awareness, logging and monitoring basics, and good habits for versioning prompts, models, and datasets
• LLM platform breadth, experience integrating multiple LLM providers, working with vector databases, and using LangChain (or similar); comfortable fine-tuning when it truly makes sense
• A track record of proactive problem framing, identifying problems and proposing solutions on your own, rather than waiting to be told exactly what to build
• Compliance or security experience, or a strong interest in it, is a genuine plus as we move upmarket
• Comfortable in a lean team where you own outcomes, not just tickets