Founding Member of Technical Staff

Mercora; Zug; Hybrid; CHF 150.000 - 230.000; Vollzeit

Benefits dieser Stelle

Significant founding equity

Daily collaboration with the founding팀

Direct line to users

Full technical autonomy

Access to cutting-edge AI infra

Zusammenfassung

Mercora, the AI operating system for physical commodity trade, seeks a founding member of the technical staff in Zug, Switzerland. You will work directly with the founding team to shape the product and write the roadmap.

You’ll own features end-to-end, gather context from users, decide what to build, ship it, measure it, and iterate as you engage with customers. The stack includes TypeScript/React on the frontend, Python on the backend, with LLMs and ML integrated into the core product.

Qualifikationen

• 3+ years building full-stack web applications in production.
• 1+ years building generative AI or ML applications in production.
• Strong fundamentals in distributed systems, data modeling, and API design.
• Fluent English.

Aufgaben

• Own features end-to-end: gather context from users, decide what to build, ship it, measure it, iterate.
• Ship features, measure impact, and iterate.
• Engineers talk to customers directly.
• Own infra: CI/CD, cloud deployment, observability.

Kenntnisse

Full-stack web development

TypeScript

Python

LLM APIs

Distributed systems

Data modeling

API design

English fluency

Tools

Kubernetes

Terraform

AWS/GCP

CI/CD

Observability

Data pipelines

Jobbeschreibung

All openings

Founding Member of Technical Staff

Department Engineering

Location Zug, Switzerland

Employment type Full-time

Workplace Hybrid or Remote

Why us

Mercora is the AI operating system for physical commodity trade. ~$8 trillion/year in transactions, still running on spreadsheets, email, and disconnected legacy systems. We’re building the system of record this industry has never had.

About The Role

One of the first engineering hires. You work directly with the founding team. There is no roadmap handed to you. You help write it.

You’ll own features end-to-end: gather context from users, decide what to build, ship it, measure it, iterate. Engineers talk to customers directly.

The stack today is TypeScript/React on the frontend, Python on the backend, with LLMs and ML integrated into the core product. That will evolve, and you’ll have a say in how.

What we're looking for

• Shipped AI-powered products for real users using TypeScript, Python, and LLM APIs (OpenAI, Claude, Gemini).


• Built and deployed complex data pipelines or multi-step AI workflows to production.


• Strong opinions on how to build reliable AI features, not just demos.


• Comfortable owning infra: CI/CD, cloud (AWS/GCP), observability, deployment.


• Can learn a complex domain fast. Commodity trade is dense and you’ll need to get fluent in trade lifecycles, document structures, and operational workflows quickly.


• Commercial instinct. You think about what moves the needle for customers, not just what’s technically interesting.


• You know when to cut corners and when to be rigorous. Move fast at the edges, build carefully at the core.


• You don’t wait for tickets. You see what needs doing and do it.

Must-haves

• 3+ years building full-stack web applications in production.


• 1+ years building generative AI or ML applications in production.


• Solid fundamentals in distributed systems, data modeling, and API design.


• Fluent English.

Nice-to-haves

• Founding engineer experience at a high-growth startup, or founder background.


• Commodities, energy, logistics, supply chain, or fintech domain experience.


• Deep infra knowledge (Kubernetes, Terraform, streaming pipelines, data warehouses).


• AI side projects with real traction (users, stars, downloads).


• Experience working directly with enterprise clients.

What you get

• Significant founding equity.


• Daily collaboration with the founding team.


• Direct line to users. Your code ships to commodity trading firms making high-stakes decisions.


• Full technical autonomy. You pick the tools, you own the architecture.


• Access to cutting-edge AI infrastructure: LLM pipelines, agentic workflows, document intelligence at scale.