Founding Engineer (AI/ML, Full-Stack) - On-site Munich

clera Germany
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AI Summary

Seed-funded AI startup seeks a Founding Engineer to build core product and technical infrastructure for enterprise customers. Responsibilities include developing full-stack components, designing data pipelines for video and unstructured data, and integrating LLM/VLM models. Requires 3+ years of full-stack experience, strong Python/FastAPI skills, and experience with video processing and LLM/VLM integration. This on-site role in Munich offers significant ownership, equity, and visa sponsorship.

Key Highlights
Founding-level role with significant ownership and equity
Focus on automating knowledge work by cloning expertise
On-site position in Munich with visa sponsorship available
Key Responsibilities
Build product features and core technical infrastructure for enterprise customers
Design and implement data pipelines to ingest, convert, and aggregate large volumes (1,000+ hours) of video and other unstructured data into a data lake
Integrate LLM and VLM pipelines into product workflows
Develop full-stack components using Python and FastAPI
Collaborate directly with customers (PE portfolio company teams) to map processes and identify automation opportunities
Support a land-and-expand go-to-market strategy by enabling scalable integrations
Technical Skills Required
Python FastAPI RESTful APIs Video Processing Video Analytics Data Pipelines LLM VLM Cloud Infrastructure
Benefits & Perks
Significant equity
Visa sponsorship available
Salary range: $80,000 – $120,000 USD (or equivalent) annually
Nice to Have
Experience working directly with enterprise or B2B customers to scope and solve technical problems
Background in AI/ML automation for knowledge-work or professional services verticals

Job Description


About The Role

A seed-funded AI startup in Munich is looking for a Founding Engineer to join on-site and help build core product and technical infrastructure for enterprise customers. The company is focused on automating repetitive knowledge work by cloning expertise — enabling teams to unlock higher-value output. This is a founding-level role with significant ownership, equity, and direct impact on product direction.

What You'll Do

  • Build product features and core technical infrastructure for enterprise customers
  • Design and implement data pipelines to ingest, convert, and aggregate large volumes (1,000+ hours) of video and other unstructured data into a data lake
  • Integrate LLM and VLM pipelines into product workflows
  • Develop full-stack components using Python and FastAPI
  • Collaborate directly with customers (PE portfolio company teams) to map processes and identify automation opportunities
  • Support a land-and-expand go-to-market strategy by enabling scalable integrations

What We're Looking For

Must-haves

  • 3+ years of full-stack engineering experience
  • Strong proficiency in Python and hands-on experience building production-ready RESTful APIs with FastAPI in scalable systems
  • Deep experience designing and implementing video processing data pipelines and related video analytics workflows
  • Experience building data pipelines to convert large volumes of unstructured video data into structured, queryable formats
  • Hands-on experience integrating, fine-tuning, and deploying LLMs and VLMs in production pipelines
  • Familiarity with cloud infrastructure and deployment
  • Early-stage startup experience with a demonstrated ability to operate with high ownership and minimal process
  • Strong written and verbal communication skills; comfortable working in small, cross-functional teams

Nice To Have

  • Experience working directly with enterprise or B2B customers to scope and solve technical problems
  • Background in AI/ML automation for knowledge-work or professional services verticals

Compensation & Benefits

  • Salary range: $80,000 – $120,000 USD (or equivalent) annually
  • Significant equity as a founding team member
  • Visa sponsorship available

Location

This role is on-site in Munich, Germany. Remote work is not available for this position.

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