Full Stack Product Engineer

About Incisiv

Incisiv is a leading insights-driven advisory firm focused on helping consumer-facing industries accelerate digital transformation with clarity and confidence. We specialize in data-backed research, benchmarking, and decision frameworks across omnichannel retail, consumer experience, and operations.

Our work combines large-scale consumer and executive research with deep industry expertise to help enterprises identify what truly drives performance, prioritize investments, and close the gap between strategy and execution. Incisiv partners with leading brands, technology providers, and industry bodies to deliver practical, outcome-oriented insights that shape real-world decisions.

About the Role

We're building AI-powered analytics and generative platforms for industry insights.

We need a product engineer who can own the technical layer end-to-end. You'll work on strengthening our platform architecture, establishing scalable engineering practices, and accelerating feature development.

This is the first engineering hire. You'll work directly with the founding team to translate business needs into technical solutions. If you need detailed specs to start working, this isn't the right fit. If you can hear a business problem and start sketching a technical approach, keep reading.

What You'll Work On

• Knowledge systems : RAG pipelines, embedding strategies, retrieval optimization. Making large structured and unstructured datasets useful to LLMs.
• Agentic workflows :
  Multi-step AI processes that run reliably. Orchestrating tool calls, maintaining state, handling failures gracefully.
• Adaptive interfaces : UIs that reshape based on context and data. Think Notion, Linear, or Perplexity. Dynamic layouts, inline AI-generated content, seamless interactions.
• Platform foundations :
  Building reusable components, improving architecture, setting up patterns that scale.

What We're Looking For

Must Have

• Strong React and Type Script fundamentals
• Deep understanding of RAG: chunking, embeddings, retrieval, vector databases. Production experience, not just tutorials.
• Experience building agentic or multi-step LLM workflows. You understand the principles even if the frameworks keep changing.
• Comfort with ambiguity. You'll often need to figure out what to build, not just how to build it.
• Ability to translate business problems into technical architecture. This is the real differentiator.

Important But Learnable

• Our specific stack (Supabase, Postgre
  
  SQL, Recharts, etc.)
• Document generation (PDF, DOCX, presentations)
• Specific agent frameworks (Lang Graph, CrewAI, etc.)

Behavioral Fit

• Ships fast, iterates, doesn't over-engineer
• Self-directed. You'll own the technical domain.
• Low ego. Willing to learn unfamiliar tools, ask basic questions, do what needs doing.
• Good communicator. Can explain technical tradeoffs to non-technical key business stakeholders.

What We Offer

• Ability to shape the technical layer from day one
• Direct collaboration with the founding team
• Work on AI-native products using RAG, agents, and generative interfaces
• Competitive salary based on experience

How to Apply

If you believe you fit the profile, please send your résumé and a two-minute video introduction to

. Applications without a video will not be considered. Also need:

• A link to something they've built (Git Hub, live app, or write-up)
• A short note on a RAG or agentic AI project they've worked on