Senior Applied AI Engineer arbeitnow Jupus Germany · 10/13/2026

Primetime; Deutschland; Remote; EUR 90.000 - 150.000; Vollzeit

Benefits dieser Stelle

Fully Remote

Top Equipment — MacBook & accessories

Wellbeing Perks — Urban Sports Club

Zusammenfassung

Primetime in Germany seeks a Senior Applied AI Engineer to accelerate our core AI team. You will own production AI features, from design to deployment, with a focus on practical, user-facing systems for legal tech workflows.

You'll work on generative AI, RAG pipelines, and agentic workflows, collaborating with engineering and product to ship reliable AI capabilities and improve observability and evaluation across platforms.

Qualifikationen

• Extensive hands-on experience building and deploying generative AI systems in production.
• Experience with RAG architectures (embeddings, retrieval, ranking).
• Experience designing and deploying agentic systems or AI agents in production.
• Familiarity with LLM observability tools (LangSmith, Langfuse) and designing evaluation pipelines.

Aufgaben

• Architect and implement production-ready generative AI and LLM-based solutions within our product suite.
• Design and develop agentic systems that automate workflows and perform multi-step tasks.
• Build and maintain RAG pipelines enabling users to interact with documents and case files.
• Implement evaluation, testing, and observability for AI systems to ensure reliability and improvement.
• Establish best practices for AI development, testing, and deployment across products.
• Initially handle AI development hands-on as a core technical contributor in a small, fast-moving team.

Kenntnisse

Generative AI in production

RAG architectures

Agentic systems

LLM observability

Python

LangSmith

Langfuse

Production features

Tools

LangSmith

Langfuse

Jobbeschreibung

We’re seeking a driven Senior Applied AI Engineer to join one of the fastest-growing legal tech companies in Europe as we expand our core AI team.

This role focuses on applied generative AI in a production environment — building systems such as RAG pipelines, agentic workflows, and AI features used directly by lawyers.

Reporting to the AI Lead, you’ll work hands-on from architecture to implementation, collaborating with the Head of Engineering and product teams to ship reliable AI functionality while improving our LLM infrastructure, observability, and evaluation workflows.

For an engineer with practical experience building and deploying generative AI systems, this is an opportunity to create real product impact and help shape how AI evolves across the company.

Your Challenge and Opportunity in This Role

You’ll help define how AI is built and shipped in a fast-moving product environment. As a core AI Engineer, you’ll turn modern generative AI techniques into production‑ready systems that deliver real value to users.

You will contribute to capabilities such as document understanding, document generation, and conversational interfaces over legal case files. Expect strong technical ownership, fast iteration, and a clear focus on building practical AI systems that improve productivity for law firms.

Tasks

Architect and implement production‑ready generative AI and LLM‑based solutions within our product suite

Design and develop agentic systems that automate workflows and perform multi‑step tasks within the JUPUS platform

Build and maintain RAG pipelines enabling users to interact with documents and case files

Implement evaluation, testing, and observability for AI systems to ensure reliability and continuous improvement

Establish best practices for AI development, testing, and deployment across products

Initially handle AI development hands‑on as a core technical contributor within a small, fast‑moving team where engineers own problems end‑to‑end and ship quickly

Cross‑functional Collaboration:

Work closely with product, design, and engineering teams to integrate AI capabilities into real product workflows

Translate complex AI concepts into practical product features and communicate them clearly to both technical and non‑technical stakeholders

Requirements

Technical Expertise:

Extensive hands‑on experience building and deploying generative AI systems in production

Strong experience with RAG architectures (embeddings, retrieval, ranking)

Practical experience designing and deploying agentic systems or AI agents in production

Experience with LLM observability and evaluation tools (e.g., LangSmith, Langfuse) and designing evaluation pipelines for LLM systems

Strong programming skills in Python and solid software engineering practices

Experience designing LLM systems beyond simple API integrations, including retrieval pipelines, orchestration logic, and tool/agent workflows

Experience implementing AI features in real product environments, not purely research or academic settings

Ability to translate modern AI techniques into reliable, user‑facing product functionality

Other requirements:

You must be located in the CET -2/+2 zone for this role!

You must have at least 4 years of professional experience in AI

You must have deployed AI systems such as RAG pipelines or agentic systems into production

Foundational Impact – Help build and scale the core AI capabilities of JUPUS from the ground up

Technical Ownership – Work directly on the systems powering AI features across multiple products

Growth Environment – Build production AI systems at the cutting edge of generative AI and agentic workflows

Leadership Visibility – Flat hierarchy with direct access to the Head of Engineering and CTO, reporting to the AI Lead

Benefits

• Fully Remote – Enjoy the flexibility of working from anywhere
• Top Equipment – State‑of‑the‑art MacBook plus all the accessories you need
• Wellbeing Perks – Urban Sports Club membership to support your healthy lifestyle

If you're passionate about building practical AI systems, shipping agentic workflows, and creating real impact for users through generative AI, we’d love to hear from you.

This overview was written from the original listing to help you understand the role. Always confirm the specifics on the employer’s application page.