Software/AI Engineer
Build the agent runtime. Sandboxed execution, tool orchestration, memory, the closed loop where the agent checks its own work.
Build the agent runtime. Sandboxed execution, tool orchestration, memory, the closed loop where the agent checks its own work.
& Verantwortlichkeiten Entwicklung und Implementierung von AI- und Agenten-Lösungen von der Idee bis zum produktiven Einsatz Konzeption mode
At 5Plus (part of Pentadoc Group), we build production-grade AI systems that solve real operational problems for our customers.
01 · Why this role exists Invest in Values.
KI-Agenten arbeiten rund um die Uhr, werden nicht müde und erledigen wiederkehrende Aufgaben zuverlässig und mit weniger Fehlern.
Wir schreiben dir, sobald eine neue geprüfte Stelle dazukommt. Höchstens eine Nachricht am Tag, und nur, wenn es tatsächlich etwas Neues gibt.
Abmelden mit einem Klick, jederzeit. Keine Weitergabe an Dritte.
Du entwickelst die Software unserer Bestückungs- und Inspektionsmaschinen weiter: Bewegungssteuerung, Bildverarbeitung, Kalibrierung (C#,.NET).
Multi-Agent-Architektur & Orchestrierung Konzeption und Umsetzung produktionsreifer Multi Agent Systeme mit klar definierten Strategien für
Multi-Agent-Architektur & Orchestrierung Konzeption und Umsetzung produktionsreifer Multi Agent Systeme mit klar definierten Strategien für
Multi-Agent-Architektur & Orchestrierung Konzeption und Umsetzung produktionsreifer Multi Agent Systeme mit klar definierten Strategien für
Forward Deployed heißt bei uns: Du bist Beobachter, Architekt und Entwickler in einer Person.
Das verantwortest du: Das Python-Backend, das unsere medizinische Echtzeit-Dokumentation in Produktion antreibt Live-Transkription echter Ar
im Team You design and deliver applied AI solutions - from understanding client needs and defining project scope to developing prototypes, p
Verantwortet Logistik-Features von der Idee bis Production und steuert Agents über Specs, mit Evals, Guardrails und Qualitätsprüfung.
RAG-Pipeline & KI: Architektur und Entwicklung der serverseitigen RAG-Pipeline, von der Query-Verarbeitung über Embedding und Vector Search
Als AI Engineer (w/d/m) schreibst du nicht nur Notebooks und Prompts, du baust produktive GenAI-Systeme: Agenten, RAG-Pipelines, LLM-getrieb
Baut No-Code-Automationen mit n8n, Make und Zapier, entwickelt KI-Agenten, pflegt Airtable-Datenbanken und betreut Kunden technisch.
Aufgabenbereiche Entwicklung von KI-Automationen mit No-Code / Low-Code Tools wie n8n, Zapier, Make Entwicklung von KI-Agenten und Prompt En
Spezialisierung auf Retrieval-Augmented Generation (RAG), Chatbots, agentenbasierte Systeme und Large Language Models (LLMs) Konzeption, Ent
Das waren alle 18 Jobs zu dieser Auswahl.
Warum dieser Job gelistet ist
Eindeutige KI-Rollenbezeichnung im Stellentitel. Prüfverfahren ansehen
Build the agent runtime. Sandboxed execution, tool orchestration, memory, the closed loop where the agent checks its own work. The layer that turns a sentence in Slack into a real action against a real API — and verifies it landed. Ship integrations. OAuth, webhooks, schema mapping, error handling. The bar is that it works on the customer s actual data on day one, not on a fixture. Run the infrastructure. Container orchestration, autoscaling, cost per task. The product stays fast and cheap because you re paying attention to it. Ship product. Features that go directly to users through Slack and Teams. You ll see people using what you built within hours. Whatever needs building. Small team, large surface. You ll work on things that aren t in this document. How you ll know it s working You ship to production every day and the changelog has your name on it. A feature you built is the reason a customer closed. When something breaks at 3am, you can fix it because you understand the system end to end. The founders are writing less code because you ve taken over surfaces they used to own. Week one: ship something to production. Take ownership of a live surface. You Personally built or significantly modified an AI agent harness — you can describe the trade-offs you made and why Made an agent reliably close the loop: tests, linters, typecheckers, verification, whatever it took to get the agent to check its own work instead of hallucinating success Built custom skills, CLIs, or MCP servers to make your own agentic coding faster — you don t just use the tools shipped to you Agentic coding is your daily workflow. Informed opinions about which models, harnesses, and tools to reach for and when — stress-tested across the frontier, not just settled on one Systems thinking: hard technical trade-offs, understanding how things break at scale, good judgment about what s worth doing well vs. fast Range: agent runtime to React component to deployment script in an afternoon Genuine interest in how AI actually works — you ve read papers, read other people s prompts, have opinions about evals This role doesn t work without agentic coding fluency. If AI-assisted development isn t already how you work, you ll be behind on day one. Why this role is different No layers. You work directly with both founders. Decisions get made in the room, not in a ticket. The agent is the product. You re not bolting AI onto something — you re building the thing customers came for. Every reliability win, every new tool, every memory improvement shows up in retention the next week. Volume that forces you to be good. 600K+ tool calls a day means the lazy answer breaks in production immediately. The feedback loop is hours, not quarters. Ship in the morning, customer uses it in the afternoon, you see what worked by end of day. Even better if Previous founder or early-stage builder
TypeScript. React. Python. AI-assisted development. Container orchestration
Experience building or significantly modifying AI agents Fluency in agentic coding workflows Experience with systems thinking and technical trade-offs Ability to ship to production quickly Onsite work in Munich, New York, or Warsaw Build and enhance AI agents for Slack and Teams, integrating tools, ensuring reliability, and shipping code to production daily in a fast-paced, small team environment. The short version You re the person who makes the product do more things, for more customers, more reliably. You ve built agents before — runtime, tools, memory, evals — and you have opinions about what makes them work. You ship to production the day you wrote the code. AI-assisted development is how you work by default, because that s how you re fastest. If you ve never built an agent, this isn t the role. We re hiring people who already have the muscle and want to build the agent everyone else will try to copy. What s actually going on Someone in Slack asks the product to reconcile their Stripe payouts against their books. It does it, live, in under a minute. The customer tells their network. Two more teams sign up that week. That s the loop. Your job is to make it happen more often, across more surfaces, more reliably. 600K+ tool calls a day. Volume curve is steep. Connections to thousands of tools — Salesforce, Notion, Stripe, QuickBooks, HubSpot, Shopify, whatever customers ask for next. Each new integration unlocks a new shape of customer. Each reliability win compounds.
Client Information An innovative company is the AI coworker. It lives in Slack and Microsoft Teams, connects to thousands of tools, and does real work for real companies: finance, marketing, ops, engineering. We re building the product that replaces half the SaaS stack with a single teammate.
Software/AI Engineer Build and enhance AI agents for Slack and Teams, integrating tools, ensuring reliability, and shipping code to production daily in a fast-paced, small team environment. Mid-Senior. Full-time.
Remote. Germany
Interesse an dieser Position?
Die vollständige Anzeige und das Bewerbungsformular liegen beim Arbeitgeber.
Zur OriginalanzeigeKI in bestehende Software und Abläufe bringen: Agenten, RAG-Systeme, Schnittstellen, automatisierte Arbeitsketten.