AI Product Engineer

Department: Backend Development

Location: Europe (remote)

Employment Type: FullTime

Team: Product / Engineering
Location: Remote / Europe

About the Role 🚀

We’re looking for an AI Product Engineer who can turn raw ideas into real, working products—fast.

This is a hands-on builder role at the intersection of product thinking, engineering, and AI-native development. You’ll partner with product managers, designers, and engineers to explore new ideas, rapidly prototype solutions, validate user value, and help scale the strongest concepts into production.

You should be deeply comfortable working with AI coding agents like Claude Code and Codex as core tools—not just for speed, but for building reliable, production-ready systems. This role isn’t about “vibe coding”—it’s about combining AI-driven velocity with strong engineering and product judgment.

You’ll build across multiple domains, including e-commerce, e-learning, and fintech/trading, with the freedom to experiment and the responsibility to ship.

What You’ll Do 🛠️

• Turn ambiguity into execution
  Translate rough ideas into clear product concepts, flows, and working prototypes.

• Build fast with AI agents
  Use tools like Claude Code, Codex, and similar workflows to ship MVPs, experiments, and production components quickly.

• Design AI-native products
  Create experiences where AI is core to the product—not just an add-on.

• Develop agent workflows
  Design systems that combine prompts, tools, retrieval, memory, and orchestration patterns effectively.

• Bridge prototype → production
  Know when something is “good enough” to validate—and when it needs to be hardened for scale.

• Collaborate cross-functionally
  Work closely with product, design, and engineering to prioritize high-impact problems and ship quickly.

• Build across the stack
  Contribute to frontend, backend, integrations, internal tools, and automation as needed.

• Ensure reliability
  Implement lightweight evals, QA checks, and monitoring for AI-driven systems.

• Document and scale learnings
  Capture insights, reduce handoff friction, and turn experiments into repeatable patterns.

What We’re Looking For 🔍

Core Strengths

• Strong product instincts — you simplify complexity, identify user pain, and focus on what matters.

• Strong builder mindset — you prototype first, refine later.

• AI-native development experience — hands-on with tools like Claude Code, Codex, or similar.

Technical & AI Expertise

• Deep experience with AI coding agents:

  • Task decomposition, context management, output review, and iteration

  • Multi-file changes, tool usage, and workflow orchestration

• Solid understanding of agentic systems, including:

  • Prompt design and decomposition

  • Tool integration and context strategy

  • Structured outputs and failure handling

• Familiarity with agent orchestration patterns:

  • Single-agent vs multi-agent tradeoffs

  • Sequential, concurrent, and handoff workflows

• Experience integrating APIs, tools, and data systems

• Ability to move from prototype to production with sound engineering judgment

Ways of Working

• Comfortable operating in fast-moving, ambiguous environments

• Strong communicator across both technical and non-technical stakeholders

• Ability to contribute across multiple product domains

Ideal Candidate 🌟

The ideal candidate combines the speed of AI-driven development with the discipline of strong engineering and product thinking.

You don’t just generate code—you:

• Review, test, and refine it

• Structure it for maintainability

• Know when to move fast—and when to slow down

You understand the difference between quick experiments and systems that can scale—and you know how to build both.

Nice to Have ➕

• Experience building AI assistants, copilots, or agent-based systems

• Familiarity with evals, retrieval, tracing, and observability

• Experience with product analytics and experimentation

• Full-stack development experience

• Background in e-commerce, edtech, fintech, or trading systems

• Experience building internal tools or zero-to-one products

• Exposure to regulated or high-stakes environments

How Success Will Be Measured (First 90 Days) 📈

• Ship multiple high-quality prototypes and internal tools

• Significantly reduce time from idea → testable product

• Demonstrate strong judgment in:

  • When to use AI agents

  • When to simplify

  • When to productionize

• Create reusable patterns for AI-assisted product development

• Contribute meaningfully across multiple product areas