(Senior) AI/LLM Engineer

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Senior From the posting source checked Jun 20, 2026

Work mode

Onsite From the posting source checked Jun 20, 2026

In-office days

5 days From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Company

Company stage

Early From the posting source checked Jun 20, 2026

Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

(Senior) AI/LLM Engineer Munich | OnSite Mercura (YC W25) helps the companies that build the real world move at software speed, automating the back-office work that runs the $12 trillion industry behind every hospital, school, and power plant. We started with one of their biggest bottlenecks - turning messy technical requests into accurate quotes - and grew to $2M ARR in our first year. With a team of 16, we're now targeting $10M by the end of 2026 as well as our expansion into the US. ABOUT THE ROLE As an AI/LLM Engineer, you will play a key role in building agentic AI systems end-to-end. This is a fast-paced, hands-on role for engineers with high agency, strong technical depth and founder mindset. You'll work on building reliable AI systems in production - from retrieval and LLM orchestration to tool-using agents and product integration. If you're a passionate builder who excels at the intersection of LLMs, data systems, AI, data engineering, and full-stack development, this is your opportunity to shape how users interact with AI in real-world workflows. WHAT YOU WILL BE WORKING ON - Agentic Systems: Design and build LLM-powered agentic systems end-to-end, from experimentation to production deployment - Retrieval & Context: Build retrieval and context pipelines (RAG, hybrid search, structured retrieval) to enable reliable reasoning over large volumes of technical and commercial data - AI Evals: Develop evaluation and monitoring systems to measure and improve AI performance in production - Data Pipelines: Build scalable pipelines to process and structure

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