Staff AI Engineer — Agent Platform (all genders)

wingmaite; España; Remote; EUR 90,000 - 130,000; Full time

Benefits offered by this job

Flexible remote setup

Generous vacation & workation budget

Technical ownership of the platform

Job summary

Wingmaite GmbH is seeking a Staff Engineer to own the technical quality and direction of our agent platform. You will design end-to-end features, from the agent to the backend, and work closely with our CTO as a technical sparring partner.

We work as one team across design, product, and engineering, building reusable components and ensuring decisions are well documented. Flexible remote setup and strong ownership are offered.

Qualifications

• Shipped multi-step, tool-using LLM agents to production.
• Know when sub-agents help, how to build evals, and why retrieval fails.
• Fluent in Python and productive in TS/Node (NestJS is a plus).
• PostgreSQL and data modeling.
• Use AI coding tools such as Claude Code every day.
• Write clear specs and explain trade-offs to non-engineers.

Responsibilities

• Design the agents: plan, use tools, handle multi-step work, and define where humans intervene.
• Connect agents to company knowledge and decision-makers.
• Ensure reliability: citations, visibility controls, and safe action.
• Track quality: build evals, monitor costs, keep model choices current.
• Ship end-to-end: build features from the agent to the backend.
• Keep architecture consistent: document decisions, review designs with teams.

Skills

LLM agents

Retrieval handling

Python

TypeScript

PostgreSQL

AI tooling

Specs & trade-offs

Tools

LangGraph

AWS Bedrock

Vertex AI

Langfuse

Knowledge graphs

Job description

wingmaite captures the knowledge companies never write down: who decides what, how work actually gets done, and why decisions were made. Our AI agents use that knowledge to answer questions and get work done.

We're looking for a Staff engineer to own the technical quality and direction of our agent platform. You'll build features end to end, from the agent into the backend. You won't manage people. You'll work closely with our CTO as a technical sparring partner.

What You'll Do

• Design the agents: Decide how our agents plan, use tools and handle multi-step work, and where people need to step in. Build reusable components so each new use case doesn't need its own system.
• Connect agents to company knowledge: Build how that knowledge reaches the agents, together with the people who decide what it should contain.
• Make answers reliable: Agents should be correct, cite their sources, show people only what they're allowed to see, and know when not to act.
• Track quality: Build evals, monitor quality and cost, and keep our model choices up to date.
• Ship end to end: Build features from the agent through to the backend yourself.
• Keep the architecture consistent: Set the patterns others build on, document decisions, keep specs current, and review designs with engineering, product and design.

How We Work

We build features as one team: design, product, engineering and AI together, from the first idea to production. You'll help shape a feature while it's still a problem and stay with it until it works for users. Agents depend on the knowledge behind them, so we build both as one system. We write decisions down and discuss disagreements openly.

What This Role Is Not

A management role, a prompt-engineering role, or an infrastructure or security role.

Must-Haves

• You've shipped multi-step, tool-using LLM agents to production (LangGraph or similar)
• You know when sub-agents help, how to build good evals, and why retrieval fails
• Fluent in Python and productive in TypeScript/Node (NestJS is a plus)
• PostgreSQL and data modeling
• You use AI coding tools such as Claude Code every day
• You write clear specs and can explain trade-offs to people who aren't engineers

Nice-to-Haves

• None of these are required, but they'll help you get up to speed faster:
• You've connected agents to tools and data through MCP
• You've worked with knowledge graphs or other ways of modeling how people, work and information relate
• You've run models in production on AWS Bedrock or Vertex AI
• You've traced and debugged agents with LLM observability tools such as Langfuse
• You speak German

Who You Are

• You've set technical direction beyond your own work, and others build on your patterns
• You start from what users need and what could go wrong, then choose the tools
• You care whether the system still makes sense in a year
• You're happy to do backend work when a feature needs it
• You want influence through your work, not through a title
• You like working with designers and product people
• You enjoy technical debate and change your mind when the other argument is better

What We Offer

• Flexible remote setup
• Generous vacation & workation budget
• Technical ownership of the platform at the core of wingmaite's product