Lead Full-Stack Engineer

Userflow; United States; On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Competitive compensation package

Job summary

Userflow is seeking a Lead Full-Stack AI Engineer who will focus on the development of AdoptionAgent. This role is pivotal in shaping how product adoption is redefined within the context of AI.

Your primary duties include shipping AI-first solutions, setting AI direction, and transforming the engineering workflow to adopt AI processes. Strong expertise in both frontend and backend technologies is required, particularly in React and Elixir.

Qualifications

• Proven ability to build and ship LLM-powered features.
• Experience with setting up AI-augmented CI/CD pipelines.
• Strong track record of improving team processes.

Responsibilities

• Lead the development of AdoptionAgent end-to-end.
• Define AI engineering practices at Userflow.
• Guide the adoption of AI workflows in CI/CD.

Skills

AI feature shipping

AI-native development workflow

Cross-stack contributions

Tools

React

Elixir

WebSocket technology

Job description

Software is being rebuilt from scratch. The companies that built the last era of onboarding tools were designed for a world of authored flows and human users. That world is ending. AI-native apps, agentic workflows, and users who expect outcomes rather than instructions are rewriting what "product adoption" means. Userflow is making a deliberate bet to become the adoption layer between any software and any user — human or agent. This role is how we ship that bet.

Why this role exists

We're building AdoptionAgent - the next evolution of Userflow's in-product Adoption Agent alongside AI features inside the Userflow builder. These two surfaces are how we believe the product adoption category gets rebuilt over the next 24 months: from authored flows toward agentic experiences that adapt to each end-user in real time.

This is a net-add role. We're hiring a Lead-level full-stack AI engineer who can do three things in this priority order:

• Ship AI-first solutions end-to-end, in partnership with other engineers, PM, and QA.
• Set the AI direction at Userflow — agent UX patterns, prompt engineering, eval mindset, what "good" looks like for AI features here.
• Transform how our engineering org ships — AI-augmented CI/CD, AI code review, IDE-native AI workflows — so every team gets faster, not just yours.

You will lead by shipping, by setting standards, and by raising the bar for the engineers around you.

What you'll own

• AdoptionAgent, end-to-end : the full development cycle of the agentic experience that customers' end-users interact with inside their own apps. This spans the UI, the agent orchestration, the structured map of each customer's app that gives the agent the knowledge it needs to act, and everything in between. High-stakes surface area: it's the user-facing AI Userflow customers ship to their users.
• AI engineering practice at Userflow : prompt patterns, agent UX heuristics, eval pipelines, internal tooling that makes AI-augmented work the default for both FE and BE engineers.
• Userflow's AI-native engineering workflow : defining how the org adopts AI in CI/CD, code review, and IDE-native development. You're the person who guides what "AI-forward at Userflow" actually means in practice.

What we need you to bring

These are non-negotiable. We're hiring against a small, specific pool and we'd rather hold the role open than mis-hire.

• Hands-on AI feature shipping - you've personally built and shipped LLM-powered product features. You can talk about prompt iteration, eval methodology, latency/cost tradeoffs, and when not to use an LLM. Resume mentions of "AI experience" without specifics will not pass our screen.
• AI-native development workflow - you ship in Cursor, Claude Code, Windsurf, or equivalent. You've set up AI-augmented CI/CD pipelines and AI code review (CodeRabbit, Greptile, Claude review, internal equivalents). You can articulate what AI tooling has actually changed about your work, not just that you use it.
• Track record of raising the bar around you - you've changed how a team or org ships, not just how you personally ship.
• Comfort working across the stack - you may be deeper on one side than the other (see below), but you can read, reason about, and contribute meaningfully to code on either side.

Plus, depth in one of these two areas

Frontend specialization

• React + TypeScript fluency at depth from state and rendering to where complexity should live.

Backend specialization

• Production Elixir experience at depth - operational reality of running Elixir services that real users depend on.
• At-scale WebSocket experience at significant concurrent connection counts. You understand connection lifecycle, presence, backpressure, and message delivery guarantees under real load.
• Infrastructure understanding for high-scale delivery - observability, latency, multi-tenant isolation, and the systems-level thinking needed to run real-time agentic experiences for many customers at once.
• 5-8+ years building user-facing front-end systems, with at least 3 at the Senior+/Staff level shipping product surfaces that real customers depended on.

Nice to have

• Experience with agentic systems (multi-step tool use, planning loops, agent UX patterns)
• Experience with eval pipelines for LLM features in production
• Visual builder / canvas / drag-drop product experience - Userflow's core IP is a no-code visual flow builder, so background in canvas/drag-drop products (Figma, Notion, Webflow, Framer) translates directly
• Open-source contributions to AI tooling, agent frameworks, or DX tools

Details

• Competitive compensation package
• Reports to: CTO
• Team: Stream-aligned. Embedded on the AI features team (backend, QA, PM partners) for the majority of your time, with cross-team influence on FE practice across Userflow.