Junior​/medior product engineer

What you'll do

You will ship the Azumuta product end-to-end with real ownership.

Strong full-stack engineers are very welcome. Heavy backend specialists are equally welcome, because much of what we are building is deeply backend-shaped: AI agents and orchestration, structured execution data at granular depth, deep integrations with the IT systems our customers already run, multi-tenant and on-prem deployment topologies.

Specialization in the right area is what makes a senior engineer exceptional
, rather than spread thin.

Founded in 2016,
Azumuta is a Manufacturing SaaS scale-up providing digital solutions to factories worldwide. We are building the execution platform for hybrid manufacturing
: the system that orchestrates work on the shop floor across humans, AI agents, and robotic systems
.

And the bet on top is bigger:
vision-based step verification, agentic execution supervision, autonomous continuous improvement, factory replay for model training
. None of this is slideware. It is what we are building over the coming years.

• Work instructions from video. A process engineer records a short video of an operation; our system produces a structured, version-controlled instruction the team can review and ship.

• A continuous-improvement agent. Dashboards already show deviations. We want an agent that proposes evidence-backed instruction changes: not "cycle time is up on station 3" but "rework concentrates on step 7, here is the fix and the data behind it."

• Multi-level BOMs and nested assemblies. Industrial products are deeply nested; we handle the leaves but not the tree. Data model, variant rollup, integration with engineering data, routing. Foundational, and what unlocks our most variant-heavy customers.

Our core stack today is Node.js, Type Script, React, and MongoDB on cloud infrastructure.

The upcoming work stretches it significantly: LLM and agent orchestration, MCP-style tool use, computer vision for shop-floor verification, video understanding for instruction generation, software interfaces for robots and humanoids on the factory floor, observability and deployment across multi‑tenant SaaS, private cloud, and on‑prem / air‑gapped factories.

Strong experience in Java, .NET, Go, Python or similar is fine.
Mindset matters more than prior framework experience. Learning a stack is easier than learning how to think about software at scale.

We are building the execution platform for hybrid manufacturing
: the system that orchestrates work on the shop floor across humans, AI agents, and robotic systems
.

The platform is used daily by thousands of operators across Europe to design, execute, and continuously improve work in high‑mix, low‑volume factories. The technical reality is rich: multi‑level BOMs, variant‑heavy product structures, sequence‑dependent execution, version‑controlled executable work.

And the bet on top is bigger:
vision-based step verification, agentic execution supervision, autonomous continuous improvement, factory replay for model training
. None of this is slideware. It is what we are building over the coming years.

• A real builder, with depth: 0-4 years building real software products, ideally a SaaS one. You have shipped to real users, lived through incidents, made trade‑offs around reliability, observability, and cost. Full‑stack capable, with real depth on one side:

  • Backend: distributed systems, multi‑tenant SaaS, AI and agent orchestration, integration with industrial systems, video and ML pipelines.

  • Frontend: complex application UX, real‑time interfaces, offline‑capable tablet apps, performant data‑dense dashboards.

• Building with modern AI. You are excited about agentic development, not skeptical. You already use Claude Code, Cursor, or similar agent‑based tools in your daily work to plan, write code, and test. You want to push further: orchestrate multiple agents in parallel to multiply your output while still shipping high‑quality software you and the team actually understand. Hands‑on with at least some of: agent loops and tool use, multi‑agent orchestration, evals, prompt and context engineering.
  
  You do not…