AI Solutions Lead

The Role: AI Solutions Lead at super{set}

Kana is an agentic AI platform designed for marketers, empowering enterprise brands to discover optimal audiences, refine campaigns, and maintain visibility in an AI-driven landscape. This is achieved through synthetic data enrichment, AI-powered analytics, and answer engine optimization.

We are actively building a team of AI Solutions Builders, professionals who directly engage with enterprise customers and leverage AI coding agents to develop tailored applications. This role is to lead this team of AI Solutions Engineers, setting high standards and spearheading the most intricate builds. The insights and patterns identified by this team will directly influence Kana’s core platform, making it a pivotal input into our product strategy.

This is a player-coach position, requiring you to define the methodology for AI-assisted software development, ensure quality, and manage a growing team. You will also be hands-on, directly engaging with customers, building applications with AI tools, and remaining deeply involved in the technical work. If you prefer a distant management style, this role is not for you.

We seek candidates with a product management background in adtech or martech, possessing a deep understanding of how consumer-facing brands approach audience strategy, campaign execution, and growth. While not necessarily an engineer, you should be technically proficient, capable of reading code, comprehending complex systems, and holding strong opinions on development best practices.

You will report directly to the co-founder/CTO.

This is a hybrid role, requiring 4 days/week on-site.

What You’ll Own

Customer Delivery

• Deliver high-quality marketing applications that enterprise customers will rely on in production.
• Lead enterprise engagements comprehensively: from discovery and requirements gathering to building and deploying marketing applications on Kana’s platform.
• Minimize time from discovery to live deployment through meticulous scoping and AI-assisted workflows.
• Identify recurring patterns across customer builds and collaborate with engineering to integrate them into scalable platform features.
• Undertake the most complex or critical customer builds personally, setting the benchmark for excellence.
• Ensure every application shipped by your team adheres to enterprise quality standards, including performance, reliability, and user experience.

Team Leadership

• Recruit, develop, and manage a team of AI Solutions Builders, starting small and scaling with company growth.
• Mentor the team on optimizing output from AI coding agents, reviewing generated code effectively, and engaging successfully with enterprise clients.
• Establish clear feedback loops between your team and the platform engineering team to foster continuous tool improvements.

Product Strategy for the Solutions Practice

• Synthesize insights from customer builds and collaborate closely with the CTO and platform team to determine which capabilities should be integrated as first-class products.
• Define the product strategy for the solutions practice, including the types of applications we build, how engagements are scoped, and the distinction between custom builds and core platform features.
• Identify repeatable patterns across customer engagements that can evolve into standard products or templates.
• Influence the roadmap for our AI-assisted development tooling based on observed successes and failures in the field.

The Playbook

• Develop and continually refine the playbook for AI-assisted application development, covering tool selection, prompt structuring, code review standards, quality benchmarks for AI-generated output, and handling edge cases.
• Document effective and ineffective approaches, identifying methods that yield superior outcomes for various application types.
• Stay abreast of the rapidly evolving AI tooling landscape, integrating new capabilities that significantly enhance speed or reliability.

What Success Looks Like

This is a nascent team, so expectations are dynamic. However, within 6–9 months, we anticipate a small, high-performing team consistently delivering customer applications. A well-documented playbook will be actively utilized, tested, and refined through real engagements, showing early indicators of repeatable patterns—applications and approaches effective enough to serve as starting points rather than requiring entirely new builds. The ultimate measure of success is customers receiving superior applications more rapidly, and your team demonstrating measurable improvement in their building capabilities.

What We’re Looking For

Must Have

• Product management or customer-facing product engineering experience in adtech or martech. You deeply understand how consumer brands approach audience targeting, campaign optimization, and growth from a product development perspective.
• Strong technical depth. You are proficient in reading Python, React, and SQL. You grasp API design, data modeling, and system architecture. You are the type of Product Manager engineers enjoy collaborating with because you speak their language.
• Hands-on experience building real applications using AI coding tools (e.g., Claude Code, Cursor, Copilot). You have delivered tangible results and possess informed opinions on how to maximize their effectiveness while understanding their limitations.
• Experience leading small teams in a startup or high-growth environment. You excel at hiring top talent, setting high standards, and fostering team development efficiently.
• Enterprise customer-facing experience. You are equally adept at engaging with a CMO as you are at debugging a failing build.
• A proactive bias toward direct involvement and building, rather than merely delegating tasks.

Nice to Have

• Experience establishing or scaling a solutions engineering, professional services, or technical consulting practice.
• Familiarity with synthetic data, audience enrichment, or data clean rooms.
• Background in programmatic advertising, DMP/CDP platforms, or marketing analytics.
• Proven ability to define processes and methodologies for newly formed teams.

Key skills/competency

• AI Solutions
• Product Management
• Adtech/Martech Expertise
• Enterprise Customer Engagement
• AI Coding Tools (Claude Code, Cursor, Copilot)
• Python
• React
• SQL
• API Design
• System Architecture
• Team Leadership
• Solution Delivery
• Product Strategy
• Workflow Optimization
• Synthetic Data