4 geprüfte KI-Jobs in Integration & Automatisierung

Aufgaben

im Team Designing the next generation of AP automation, with AI as the foundation. The person who decides what accounts-payable automation looks like at Springtime for the next five years, and who builds enough of it to prove the case. Architectural authority across the platform, AI at the centre of the design, and hands still in the Python.

Invoicetrack has processed invoices for enterprise finance teams for years. The product works and the customers are real. The question this role exists to answer is what comes next: how AP automation should be built when AI is the foundation of the system rather than a capability added to the edges of it.

That is an architectural question before it is an engineering one. It decides where models belong and where deterministic logic belongs, how data flows through extraction, validation and approval, what we can promise customers about accuracy and auditability, and what our platform needs to become to support any of it. You own that design, end to end, and you carry it through to production.

This is a hands-on role. You will write Python, build the prototypes that settle the hard arguments, and produce reference implementations teams can build against. Own the architecture.

Prove it in code. Own the target architecture for AI-led AP automation: where the product is going over the next three to five years, what has to change to get there. Set architectural direction across the platform: service boundaries, data flows, integration patterns, and how our.NET platform and Python AI services fit together as one system.

Stay hands-on in Python. You prototype the difficult parts yourself and write the reference implementations that show how the architecture is meant to work. Decide where AI belongs and where it does not.

Machine learning, LLMs, agentic workflows and deterministic rules each have a place. You make the call and document the reasoning behind it. Design for what enterprise finance actually requires: accuracy, explainability, auditability, data residency, security, and cost per document at volume.

Turn architecture into a roadmap with the CTO and product leadership, including migration paths, sequencing, and what we stop doing to make room. Lead through influence. Architecture reviews, design documents, pairing and mentoring across engineering teams, without a reporting line to fall back on.

Raise the engineering bar for how models, services and data pipelines are built, tested, deployed and monitored, and hold teams to it in review. Treat evaluation as an architectural concern: datasets, metrics and error analysis, so what we claim about extraction accuracy and touchless rates holds up under scrutiny. Own build, buy and model selection decisions, including the long-term cost, portability and lock-in consequences of each.

Act as our senior technical voice outside the company, with enterprise customers architects and security teams, and with ERP and integration partners.

Anforderungen

An architect who still writes the code. A track record of owning architecture at enterprise scale and carrying it through to delivery, including the parts that went wrong. Strong, current Python.

You still write production code, and you would be uncomfortable in a role where you did not. AI systems you designed, shipped and operated. Machine learning or LLM-based systems in production, and clear views on their failure modes.

Depth in distributed systems and API design: service boundaries, consistency, failure handling and performance under load. Strong relational data modelling, for example SQL Server: schema design, data integrity and query performance at volume. Cloud architecture, CI/CD and containerised deployment (Docker), and first-hand knowledge of what it takes to run and observe these systems.

Judgement about when not to use a model. You know where rules, heuristics or a smaller model beat an LLM, and can defend that choice to both engineers and executives. Influence without authority at senior level.

You have taken an engineering organisation through an architectural change and brought the people with you. Credibility with executives and customers. You can explain architecture, risk and trade-offs to people who do not write code.

Fluent in English, spoken and written. Erfahrung Ten years in software engineering, several of them at principal, lead architect or chief architect level in a product company. Ausbildung A degree in computer science or equivalent professional experience.

Das wird geboten

The minimum gross salary for this position is € €5.444 per month, as determined by the IT Collective Agreement. The actual salary will be based on your qualifications and experience. Technologien und Skills SQL Server Docker .NET Python Unsere Erwartungen an dich:

Flexible Arbeitszeiten No Dresscode Kaffee, Tee o. Ä Gute Anbindung Team Events