Backend Engineer (AI Agents)
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6 days ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
Senior Compensation
€ 160KJob location
Remote
Tech stack
Artificial Intelligence
Amazon Web Services (AWS)
Cloud Computing
Databases
Continuous Integration
Python
Performance Tuning
Systems Integration
Large Language Models
Backend
Build Management
Containerization
Api Design
Requirements
A leading AI cybersecurity start-up in Spain seeks a Senior Engineer to architect and scale agentic AI systems. This role includes hands-on backend development, ML integrations, and product direction, requiring 7+ years of experience and strong expertise in Python. Successful candidates will enjoy full remote flexibility and an attractive salary of up to €160k. Join a high-caliber team making a significant impact in the cybersecurity space., * 7+ years backend engineering experience.
- Strong Python backend expertise including API design and database architecture.
- Experience integrating LLMs or AI services into production systems.
- Familiarity with agent frameworks such as LangChain or LlamaIndex.
- Solid cloud experience, ideally AWS, with CI/CD and containerisation experience.
- Strong understanding of scalable systems design and performance optimisation.
- Experience building secure, production-grade systems.
- Comfortable operating in high-ownership, fast-moving environments., Python backend expertise API design Database architecture Integration of LLMs Experience with agent frameworks Cloud experience (AWS) CI/CD Containerization Scalable systems design Performance optimization Descripción del empleo
Benefits & conditions
- Design and build scalable backend systems to support complex agentic workloads.
- Develop and productionise AI Agents solving real-world cybersecurity challenges.
- Integrate LLMs and AI services into robust, secure production environments.
- Own features end-to-end from architecture and design through deployment.
- Optimise performance, reliability, and security across the stack.
- Define engineering standards and best practices as the team scales.
- Rapidly prototype new AI-driven functionality based on user feedback.
- Mentor engineers and contribute to architectural decision-making.