Data Engineer

The next generation of data infrastructure will be built for AI agents. Weld is built to be operated programmatically through APIs and MCP, so developers and AI agents can build and run the data foundations that modern companies depend on. We move data at scale across hundreds of integrations and increasingly serve as the backbone for agentic data workflows.

You can try Weld at weld.app.

The role

Most of your time is with customers. You onboard new customers, design their data setups on Weld with them, model the data that lands in their warehouse so it is ready for analytics and for agents to operate on, and unblock them when things break. You join pre‑sales calls when prospects want to talk to someone technical, and those conversations focus on making their data usable by AI agents and on plugging Weld into their agentic workflows. When customers go deeper, designing transformation layers, structuring data for agent consumption, or building agent‑driven systems on top of their warehouse, you consult with them and build alongside them. You do this work using the tools that make modern engineering fast: Claude Code for writing and refactoring, the Anthropic API for the agents and internal tooling that scale your work, and Weld itself, which you will operate through APIs and agents, the way our customers do. What you learn from customers shapes the product. You have a direct line to the founders and the engineering team, and your field insights influence what we build next, especially in how Weld exposes itself to agents through APIs, MCP, and tool interfaces.

What you will work on

• Onboard new customers and design their data setups on Weld, from pipelines to warehouse models
• Join pre‑sales calls and technical evaluations, help prospects understand how Weld fits their stack, and shape early implementations
• Diagnose pipeline issues end to end across our integrations and customer warehouses, and unblock customers fast
• Help customers model their warehouse data, so it is clean, reliable, and ready for analytics or agent consumption
• Consult with customers building agentic systems on top of Weld, helping them design transformation layers and structure data for agent consumption
• Ship internal agents and tooling with Claude Code and the Anthropic API to scale how we onboard, support, and serve customers
• Turn recurring customer problems into product improvements, and bring field insights back to the team to shape how Weld serves agentic workflows

We are looking for someone who

• Has a solid understanding of modern data infrastructure, including ETL, reverse ETL, and data warehousing
• Has experience with SQL and data modeling
• Has built systems that interact with APIs programmatically
• Has shipped something to production with LLMs or agents
• Uses Claude Code, Cursor, or similar AI dev tools every day, and has opinions about them
• Understands how modern agents are built: tool use, sub‑agents, skills, MCP, and structured outputs
• Has thought seriously about context engineering and how to evaluate agent behavior in production
• Writes Python comfortably when needed
• Communicates clearly and enjoys working directly with customers
• Experience with TypeScript is a plus
• A background in a customer‑facing technical role such as professional services, solutions engineering, forward‑deployed engineering, or analytics consulting is a plus

How to apply

Apply via LinkedIn with a short note. Include:

• A link or short write‑up of something you have built with LLMs or agents. What it does, why you built it the way you did, and what you would change if you started over.
• A sentence or two on how you use AI tools in your own workflow today.

Working at Weld

Working at Weld means real ownership of what you work on, the freedom to make decisions, and a short distance between your work and what customers see. The role is based in our office in central Copenhagen, next to the Opera. We offer a competitive salary and equity, company off‑sites, 6 weeks paid holiday, company‑paid pension and health insurance, a MacBook Pro, and a company card from day one to buy what you need.