Forward Deployed AI Engineer (m/d/w)

Building, integrating, and implementing AI systems for medium-sized businesses.

You build AI systems that actually work – RAG pipelines, agents, automations. And you don't want to disappear into a product team's backlog, but rather see directly with the customer what your solution achieves.

As a Forward Deployed AI Engineer at Neurawork, you are the technical authority in our customer projects within medium-sized businesses: you understand the customer's processes, design the architecture, deeply integrate our standard products into their system landscape, and ensure that something productive is running at the end – not just existing on slides. Because you technically know what you're talking about, you advise customers at eye level – all the way up to management.

We work according to our own Operational AI process model. We are not an automation agency nor custom software developers: we rely on standardized products as leverage and adapt them up to complete integration. We create real, measurable added value – and stand by it.

Responsibilities

What you do with us

• Technical Implementation at the Customer: Architecture, integration, and commissioning of AI solutions (LLMs, RAG, Agentic AI, automation) into existing system landscapes – cloud or on-premises

• Assess Technical Feasibility: Examine use cases for implementability, data availability, costs, and limitations, and prioritize based on impact

• Close Collaboration with Customer IT: Interfaces, data connection, security, operation

• Consulting with Technical Substance: Fundamentally advise customers from the departmental level to management – roadmaps that are technically sound

• Co-creation of our Frameworks and Products: Feed insights from projects back

• Knowledge Transfer: Live sessions from ongoing projects in our AI training with subsequent TÜV SÜD certificate and in AI Business Coaching

How we work

• Framework-driven instead of ad hoc – and you help shape the frameworks

• Standard products as leverage, adaptations up to full integration are a matter of course

• Value instead of hours – results instead of daily rates

• Direct line to the founding team, no consulting pyramid

• Presence online and offline; CEO Christoph Knöll is visible in the DACH AI scene (unplugged, TÜV SÜD, LinkedIn)

Qualifications

What we are looking for

• Degree in STEM field (e.g., Computer Science, Mathematics, Physics, Engineering) or a comparably deep technical background

• Self-built AI systems: You have personally conceived and implemented at least one AI system – e.g., a RAG pipeline, a productive agent, or a technically responsible automation

• Deep technical understanding of LLMs, retrieval, agentic AI, cloud vs. on-premises operation – including their limitations

• Proficient handling of code (e.g., Python), APIs, and data connection

• 3+ years of professional experience in technical implementation (e.g., as an engineer, data scientist, developer, technical project manager); customer contact or consulting experience is a plus

• Enjoy explaining technology in an understandable way – ideally experience with workshops, presentations, or live sessions

• Fluent German, good English

• Residency in Germany

Not a good fit for you if…

• You have a certification without a track record,

• You prefer developing strategies over hands-on system implementation,

• You haven't yet built an AI system that you can showcase.

Benefits

What we offer

• Mandate responsibility from the first project, with no layers above you

• Professional exchange with the AI elite in Germany – in our team, you are always up-to-date

• Modern tech stack and space for testing

• Visibility as an expert through our AI Business Coaching community and TÜV SÜD cooperation

• Fully remote possible – team days and customer workshops on-site, typically 2-4 days/month in the DACH region

• Direct line to management, short decision-making processes

• Market-competitive salary with rapid growth opportunities

Application: Bring Your Project!

Send us your CV and bring us your project!

Describe in 3-5 sentences the AI project you would like to show us in the second interview: What problem does it solve, how is it structured, which part did you implement yourself? A link to GitHub, demo video, or similar is welcome.

• Professional, private, or open source – everything counts, as long as you implemented it yourself.

• Confidential client projects are welcome to be anonymized or use sample data

We look forward to getting to know you and your project!

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