Staff Engineer - Full Stack (f/m/d)
Thermondo GmbH
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Details
- Unternehmen
- Thermondo GmbH
- Standort
- Berlin
- Bereich
- Sanitär, Heizung & Elektro
- Vertragsart
- Vollzeit
- Unternehmensgröße
- Große Unternehmen (250 - 999 MA)
- Aktualisiert
- 20. Juni 2026
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Informationstechnologie in Berlin: Arbeitsmarkt & Kontext
Die Position Staff Engineer - Full Stack (f/m/d) bei Thermondo GmbH ist in Berlin in Vollzeit zu besetzen. Der Arbeitgeber zählt zur Größenklasse Große Unternehmen (250 - 999 MA). In Berlin sind derzeit 3 vergleichbare Stellen im selben Berufsfeld ausgeschrieben (von 679 Handwerks-Stellen insgesamt in Berlin). Diese Stelle wurde zuletzt am 20. Juni 2026 verifiziert.
Thermondo GmbH hat aktuell 23 weitere offene Stellen auf Meistertreff ausgeschrieben — ein Indiz für aktiven Personalaufbau. Alle Stellen dieses Arbeitgebers →
Wer in Berlin nach Informationstechnologie-Stellen sucht, findet im Umfeld auch verwandte Tätigkeitsfelder mit häufig überlappenden Qualifikationen:
Stellenbeschreibung
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Firma: thermondo
UNTERNEHMENS-ID: 5076603
Stellenausschreibungs-URL:
Karrierestufe
Berufserfahren
Beschäftigungsverhältnis
Vollzeit
Tätigkeitsbereich
IT
Branchen
Erdöl und Gas
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Were looking for
At thermondo, our mission is to
decarbonize every home
, and technology is our primary lever for change.
We are disrupting a massive industry bogged down by legacy systems and manual work. This is where you come in. We build the intelligent software and automation that gives us a decisive edge, allowing us to operate at a scale and efficiency our competitors cant match.
We are looking for a Staff Engineer - Full Stack (f/m/d) to serve as a strategic technical leader. In this role, you will not just solve the problems we hand you; you will identify the problems we should be solving. You will report to a Domain Lead and act as a technically-focused peer, helping to define the vision for our platform and the AI strategies that will differentiate us in the market.
If you enjoy this
Drive cross-team technical strategy.
You will architect the high-level systems that connect our customer apps, internal tools, and data backbone, ensuring we build for long-term scalability and resilience.
Operate with high-level autonomy.
You will translate vague business objectives into concrete technical roadmaps, proactively identifying opportunities for impact without needing a Product Manager to define every step.
Lead our AI Engineering evolution.
You will co-design the patterns for integrating LLMs into our code - handling reliability, cost, and evaluation - while demonstrating to the wider organization how to build AI-native software.
Act as a force multiplier.
You will elevate the entire department by removing developer bottlenecks, mentoring engineers, and championing AI-augmented workflows.
Bridge the gap between Business and Tech.
You will partner with leadership to navigate ambiguity, translating complex architectural trade-offs into business value and leading large-scale initiatives to delivery.
And recognise yourself here
Experienced:
You have significant experience (10+ years) in software engineering, including operating at a Lead or Staff level in a modern product company.
Full Stack:
You have deep, T-shaped expertise. You are great in Python and Node.js/TypeScript. You understand backend and frontend. You can reason about data flows and architecture, and you can build them too.
'Manager of One':
You are self-directed. If dropped into ambiguity, you create clarity. You can effectively manage your time between coding, designing, and communicating without needing constant oversight.
Pragmatic:
You avoid over-engineering. You understand that 'boring technology' is often best, but you know exactly when to spend innovation tokens (specifically on AI and Cloud scalability).
Great Communicator:
You write clear, persuasive technical documents (RFCs, ADRs). You can lead a room of engineers to a consensus even when opinions differ. You can articulate the business implications of technology in a room full of VPs.
Bonus points
Production AI:
Experience deploying LLMs in production (managing context windows, prompt engineering, vector databases, and evaluation frameworks).
Event-Driven Systems:
Deep experience with asynchronous architectural patterns and specific systems like RabbitMQ, Google Pub/Sub and Kafka.
Legacy Migration:
Experience strangling a monolith or migrating legacy systems to modern cloud-native architectures without downtime.
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