Forward Deployed Engineer - Enterprise AI Transformation - Berlin - 150k

Next Ventures; Berlin; Vor Ort; EUR 90.000 - 140.000; Vollzeit

Zusammenfassung

Next Ventures is seeking a Forward Deployed AI Engineer to join the intersection of AI engineering, consulting and enterprise transformation in Berlin. You will work directly with senior stakeholders to identify high-value AI opportunities and turn ambiguous business problems into scalable technical solutions.

You’ll embed with client teams, design production-grade AI applications (LLMs, RAG pipelines, agentic workflows) and take solutions from concept through to deployment, balancing technical

Qualifikationen

• Strong foundation in software engineering, AI/ML engineering or data engineering.
• Hands-on experience building and deploying AI or ML systems in real-world environments.
• Practical experience with LLMs, RAG, retrieval systems, agentic workflows or AI applications.
• Experience designing systems around APIs, data pipelines, enterprise applications and cloud infrastructure.
• Ability to reason through architectural decisions and explain trade-offs clearly.
• Experience taking technical solutions from requirements through deployment and iteration.
• Previous consulting or client-facing delivery experience.
• Confidence to lead technical conversations with both technical and non-technical stakeholders.

Aufgaben

• Embed closely with client teams and take ownership of AI initiatives end-to-end.
• Identify and shape high-value AI use cases with business and technical stakeholders.
• Translate ambiguous operational problems into clear technical requirements and scalable solution architectures.
• Design and build production-grade AI applications, including LLM-powered systems, RAG pipelines and agentic workflows.
• Develop AI copilots, automations and intelligent workflows that solve real business problems.
• Make and defend key architectural decisions around models, retrieval, orchestration, infrastructure, security, scalability and cost.
• Integrate AI systems into existing enterprise applications, data platforms and workflows.
• Work hands-on with Python, APIs, cloud infrastructure and modern AI tooling.
• Partner with senior client stakeholders while remaining close to the technical implementation.
• Identify recurring client challenges and help turn bespoke solutions into scalable capabilities.

Kenntnisse

Python

AI/ML engineering

Data engineering

Cloud infrastructure

APIs

Tools

LLMs

RAG pipelines

Agentic workflows

Jobbeschreibung

We're looking for a Forward Deployed AI Engineer to work at the intersection of AI engineering, consulting and enterprise transformation.

This is not a role where you sit behind a backlog building isolated features..You'll work directly with senior stakeholders and client teams to identify high-value AI opportunities, turn ambiguous business problems into technical solutions, and take those solutions from initial concept through to production.

The work sits at the sharp end of enterprise AI transformation: complex organisations, real operational problems and a high bar for both technical depth and commercial impact.

What you'll do

You'll embed closely with client teams and take ownership of AI initiatives end-to-end:

• Identify and shape high-value AI use cases with business and technical stakeholders


• Translate ambiguous operational problems into clear technical requirements and scalable solution architectures


• Design and build production-grade AI applications, including LLM-powered systems, RAG pipelines and agentic workflows


• Develop AI copilots, automations and intelligent workflows that solve real business problems


• Make and defend key architectural decisions around models, retrieval, orchestration, infrastructure, security, scalability and cost


• Integrate AI systems into existing enterprise applications, data platforms and workflows


• Work hands-on with Python, APIs, cloud infrastructure and modern AI tooling


• Partner with senior client stakeholders while remaining close to the technical implementation


• Identify recurring client challenges and help turn bespoke solutions into scalable capabilities

What we're looking for

• A strong foundation in software engineering, AI/ML engineering or data engineering, with strong Python skills


• Hands-on experience building and deploying AI or ML systems in real-world environments


• Practical experience with LLMs, RAG, retrieval systems, agentic workflows or AI applications


• Experience designing systems around APIs, data pipelines, enterprise applications and cloud infrastructure


• The ability to reason through architectural decisions and clearly explain the trade-offs involved


• Experience taking technical solutions from initial requirements through to deployment and iteration


• Previous consulting or client-facing delivery experience


• The confidence to lead technical conversations with both technical and non-technical stakeholders

Nice to have

• Experience at an AI-native company


• Stronger foundations in ML, data science or predictive modelling alongside GenAI experience


• Experience in digital strategy, transformation or technology advisory


• Exposure to transaction advisory, private equity or value-creation environments


• Experience in fast-moving startup, scale-up or consulting environments

You'll probably thrive here if you...

• Prefer shipping working systems over producing slide decks


• Like taking ownership of problems without being given a perfect specification


• Can move from a client conversation to a system architecture without losing the thread


• Care about building solutions that actually get adopted and create measurable impact


• Like operating with high autonomy, responsibility and visibility

Why this role?

This is an opportunity to work on AI where the problems are messy, the stakes are real and the answer isn't already defined.

You'll have the chance to combine deep technical work with direct client exposure, working closely with decision-makers while staying hands-on enough to shape and build the solutions yourself.

If you're an engineer who wants to move beyond simply building features - and instead wants to help define what should be built, why it matters and how it gets deployed at scale - this could be a particularly strong next step.