Full Stack Engineer - AI Platform

What We're Building

Kynetiq Labs is building the intelligence layer that powers B2B inbound. Our system reads market signals from 40+ sources, assembles them into structured context per customer, and uses AI to generate strategic decisions that get smarter over time. The AI is not a feature bolted onto a SaaS app. The AI is the product. Every layer of the stack, from data ingestion to frontend delivery, is built around that intelligence core.

What You'll Work On

This is a full stack role on an AI-native platform. You'll build across every layer: backend data systems, API integrations, LLM pipelines, and the React frontend that puts intelligence in front of customers. The range is the point. At this stage, the person building the database query is the same person building the UI component that displays the result.

Backend & Data

• Build and maintain the data layer that stores signals from 40+ external sources. Multi-tenant, event-sourced, designed to compound intelligence over time. You'll write queries, optimize performance, and ensure data integrity across workspaces.
• Build the API orchestration layer. Each external integration (SEO tools, CRMs, enrichment platforms, AI search engines) has its own auth flow, rate limits, data format, and failure modes. You'll build connectors that normalize all of it into a unified schema.

AI Pipelines

• Build multi-step LLM pipelines that take structured data and produce strategic outputs. Content recommendations, signal prioritization, competitive analysis, lead scoring. You'll handle prompt design, output parsing, validation, and error recovery.
• Build autonomous agents for specific workflows. A research agent that analyzes a company in under 60 seconds. A signal detection agent that identifies opportunities from raw data. Each one needs to be reliable enough that a founder trusts its output.
• Work on context assembly. The system passes a structured context model to the LLM for every customer. What goes into that context, how it's structured, and how it evolves per customer over time directly determines output quality. You'll build the logic that makes that context increasingly precise.

Frontend

• Build and ship features on the React frontend. Dashboards, signal views, lead tracking, workspace management, auth flows. The skeleton exists. You'll make it real, connect it to live data, and make it fast.
• Build the interactive preview dashboards that prospects see before they become customers. These are personalized, data-rich, and need to load quickly at unique URLs. The preview experience is Kynetiq's primary GTM mechanism.

Infrastructure

• Own deployment, monitoring, and reliability. Serverless functions, scheduled jobs, real-time subscriptions. You'll make sure the system runs when nobody is watching.
• Build tooling for internal operations. Admin dashboards, analytics, experiment tracking. Whatever the team needs to operate and iterate faster.

Who Should Apply

#1 You're a full stack engineer who builds end to end. You can design a database schema in the morning, write an API integration in the afternoon, and fix a frontend bug in the evening. You're not precious about which layer you work on. You care about shipping the thing that matters most today.

#2 You've worked with LLMs. Not necessarily in a production system (though that's great if you have). Maybe you've built side projects, hackathon entries, or internal tools that use LLM APIs. You understand the basics: prompt design, structured outputs, context windows, token costs. You want to go much deeper.

#3 You've integrated with third-party APIs. You know that documentation lies, rate limits are real, and auth tokens expire at the worst possible time. You've built connectors that handle all of this gracefully.

You've worked with React. You can build components, manage state, handle async data, and ship a UI that doesn't feel broken. You don't need to be a frontend specialist. You need to be competent enough to build and ship frontend features independently.

#4 You want to work at a company where you see the full picture. Not a company where you own one microservice and never meet a customer. You want to understand why you're building what you're building, and you want your work to reach users fast.

What we're looking for specifically:

• 1-5 years of software engineering experience
• Strong in Python or TypeScript (ideally both)
• React experience (building real UIs, not just tutorials)
• Some experience building with LLM APIs (production or side projects)
• Comfort with PostgreSQL or similar databases
• Ability to ship independently

Bonus points if:

• You've built multi-tenant SaaS applications
• You've worked with Supabase, Vercel, or serverless architectures
• You've built multi-step LLM pipelines or autonomous agents
• You've worked at an early-stage startup (first 5-15 people)
• You have a GitHub that shows how you think and build

What we don't care about:

• Your degree or college name
• Whether you've worked at a "name brand" company
• Whether you consider yourself "frontend" or "backend" or "AI"
• Your years of experience if your projects speak louder

What You Get

Equity. Early-stage equity in a company where the platform you're building is the product. Not a support tool. Not an internal system. The actual product customers pay for.

Full stack in the real sense. Not "full stack but actually you just write REST endpoints." You'll touch databases, APIs, LLM pipelines, agent architectures, and frontend UIs in the same week. Probably the same day.

Speed. No sprint planning ceremonies that take longer than the sprint. No PRDs that take a month to write for a feature that takes a day to build. You'll ship something your first week.

• A product that's AI-native, not AI-adjacent. Most "AI" engineering roles are about adding a chatbot to an existing product. This is a platform where every layer is built around intelligence. The AI work here is structural, not cosmetic.