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This position was posted on July 10, 2026 and is likely no longer accepting applications. We've kept it here for historical reference. Check out the similar jobs below!

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Fullstack Engineer, Generative AI (Backend Focus)

Job Overview

Location

Europe

Job Type

Full-time

Category

Software Engineering

Date Posted

July 10, 2026

Full Job Description

đź“‹ Description

  • • We are growing and seeking an extremely talented software engineer to help us pioneer the future of cybersecurity.
  • • Product Software Engineering: Hands-on engineering and testing of the product in various capacities, focusing on AI Agent features.
  • • Agents Framework Engineering: Hands-on engineering and testing of the internal agent’s framework (similar to LangChain / Haystack and others).
  • • Research & Development: Stay updated with the latest in AI and AI Agents. Provide relevant insights to the team and integrate innovations.

🎯 Requirements

  • • Ideally 5+ years of experience in Python (we can consider less experienced engineers, who learn very quickly and are ready to work in the startup environment)
  • • Experience with Generative AI
  • • Experience with Generative AI Agents will be a huge plus, specifically:
  • • — implementation of Generative AI Agents using Langchain / Haystack and others
  • • — implementation of RAG using LlamaIndex and other Advanced RAG frameworks
  • • — evaluation of AI Agent Performance
  • • — integration of AI Agents into Existing Systems
  • • Cybersecurity product background: worked on security-focused software or platforms.

🏖️ Benefits

  • • Ownership over a core cybersecurity product
  • • Direct collaboration with founders and elite cyber operators
  • • High autonomy and real impact on product direction
  • • Fully remote & flexible work setup
  • • Competitive compensation

Skills & Technologies

Python
Backend
Remote
Degree Required

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About Crackenagi

Crackenagi builds and operates an AI-powered platform that automates data extraction from documents and emails for accounting, finance, and operations teams. The system ingests invoices, receipts, contracts, and bank statements, then uses machine learning to parse line items, amounts, due dates, and vendor details into structured formats that integrate directly with ERP, CRM, and bookkeeping software. Customers gain faster, more accurate processing, reduced manual entry costs, and real-time visibility into payables, receivables, and cash flow. The company serves mid-market and enterprise clients across North America and Europe through a SaaS subscription model.

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