Full-Stack Engineer, AI Platform

About the role

About Merciv Merciv is building the intelligence layer for enterprise commerce. We connect an organization's entire data landscape — internal systems, social signals, industry reports, consumer behavior — and surface the insights and automated workflows that used to take analysts weeks.

We raised $14M in seed funding, spent two years in stealth building the right thing, and we're now launching publicly. Our platform already drives 8-figure gross margin improvements for some of the world's largest retailers.

We're a lean, high-ownership team. If you want to see your work matter immediately, this is it.

The Role You'll work across every layer of Merciv's platform — from backend services processing enterprise data at scale to the frontend interfaces that make intelligence accessible and actionable. Full-stack here means full ownership: you take features from idea to production and iterate directly with enterprise clients.

This role is for engineers who are energized by breadth, who want to understand the whole system, and who see product context as a superpower.

What You'll Do

- Build and ship features end-to-end — backend in Go/Python, frontend in React/TypeScript

- Design APIs, data models, and service architectures supporting Merciv's agentic AI capabilities

- Create intuitive interfaces that translate complex enterprise data into clear, actionable workflows

- Collaborate with ML/AI engineers to bring AI-driven features to production

- Own the full lifecycle: scoping, architecture, implementation, testing, deployment, and iteration

- Work directly with enterprise customer feedback to understand real-world needs and shape the product

- Contribute to infrastructure, tooling, and developer experience as we scale

You May Be a Good Fit If

- You have 3+ years of engineering experience with meaningful work across frontend and backend

- You're proficient in TypeScript/React and at least one of Go or Python

- You have strong product instincts — you think about the user, not just the code

- You're comfortable taking a vague problem and turning it into a shipped feature

- You have experience with cloud infrastructure (AWS preferred) and modern deployment practices

- Former technical founders are encouraged to apply — we care more about what you've built than how long you've been building

Bonus points for:

- Experience with agentic AI systems, LLM integrations, or RAG architectures

- Background in enterprise SaaS, retail tech, or data-intensive products

- Familiarity with data visualization, real-time systems, or streaming architectures

- Contributions to developer tooling, CI/CD, or infrastructure automation

How We're Different Most AI platforms bolt intelligence onto existing workflows. We're building the intelligence layer from scratch — connecting every data source an enterprise touches and making it actionable in real time. Our agentic infrastructure doesn't just surface insights; it acts on them. That's a harder problem, and it's the one we're solving.