Junior AI Solutions Engineer

The Role

Kana is an agentic AI platform for marketers. We help enterprise brands find better audiences, optimize campaigns, and stay visible in an AI‑driven world – using synthetic data enrichment, AI‑powered analytics, and answer engine optimization.

We’re hiring an AI Solutions Builder to work directly with enterprise customers, understand their business problems, and use AI coding agents to build the applications that solve them. Not mockups. Not specs. Working software. This team is a strategic extension of the product. The goal is to convert customer builds into repeatable capabilities. Success is measured by how much learning maps into the platform.

Hybrid – 4 days/week

• Deliver high-quality marketing applications that customers rely on in production.
• Sit with enterprise customers to understand their workflows, pain points, and success criteria for marketing applications.
• Use AI coding agents to design and build end-to-end full-stack applications – audience builders, analytics dashboards, campaign optimization tools – within Kana’s platform.
• The most important skill in this role is the judgment of knowing when AI output is production-ready and when it needs correction.
• Review AI-generated code for correctness, performance, and architecture. Spot problems like unindexed queries, bloated API responses, or poorly structured components, then direct the AI to fix them.
• Debug by reading logs, tracing errors, and understanding enough about Python, React, and SQL to know what went wrong.
• Own the customer relationship through the build lifecycle: communicate progress, manage expectations, deliver results.
• Ensure applications meet basic enterprise standards: reliability, performance, clean data flow, and clear UX.
• Work with our platform engineering team to surface patterns, report tool limitations, and shape how we build software with AI.

This role is designed for recent fresh‑graduates up to 1 year of experience – who have been actively building with AI coding tools on their own time. We care more about demonstrated technical sharpness and deep curiosity than years of experience.

• Hands‑on experience with AI coding tools (Claude Code, Cursor, Copilot, Windsurf, Codex, or similar). You understand their strengths, failure modes, and how to get the best output from them.
• Technical literacy: you can read Python, React/JavaScript, and SQL. You can follow a stack trace, understand why a SELECT
  * on a million rows with no WHERE clause is a problem, and recognize what good code looks like – even if you’re not writing production code yourself.
• The ability to translate business requirements into something buildable. Whether from a CS degree, PM experience, consulting, or self‑taught – you know how to listen to a customer and figure out what they actually need.
• Strong communication skills. You’ll talk to enterprise stakeholders and engineers on the same day. You know that the quality of your input to an AI system determines the quality of its output.
• Systems thinking. You naturally consider data flow, edge cases, performance, and user experience.

• CS degree or equivalent practical experience.
• Experience in a customer‑facing B2B role: solutions engineering, technical consulting, product management.
• Familiarity with marketing technology, SaaS platforms, or enterprise software environments.
• Exposure to data modeling, API design, or systems architecture concepts.

The Recent CS Grad Who Builds Differently. You finished your degree and immediately realized the way you build software is fundamentally different from how your professors taught it. You’ve been using AI coding agents for personal projects, hackathons, or freelance work. You understand CS fundamentals and can apply them to evaluate AI-generated output. You want a job where this skill set is the job.

Send us something that shows how you build with AI. A project, a demo, a write‑up of your process – anything that demonstrates you’re already doing this work. That will tell us more than a resume.