Applied AI Engineer
Posted 13 Oct 2026
Advertised as “Senior Applied AI Engineer”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 4+ yrs
- Management level
- Individual contributor
- Employment
- Remote
- Contract
- Full-time
No salary listed for this role.
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
AI Strategy & Implementation:
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Architect and implement production-ready generative AI and LLM-based solutions within our product suite
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Design and develop agentic systems that automate workflows and perform multi-step tasks within the JUPUS platform
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Build and maintain RAG pipelines enabling users to interact with documents and case files
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Implement evaluation, testing, and observability for AI systems to ensure reliability and continuous improvement
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Establish best practices for AI development, testing, and deployment across products
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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