Senior Backend Engineer, AI Platform
New
J
JobgetherVacation rental SaaS
Must be physically based within Europe or the Middle East and North Africa (MENA) region.Full-TimeSenior
Salary not disclosed
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Job Details
- Experience
- At least 5 years of professional experience in backend engineering
- Required Skills
- PythonRESTful APIsLangChain
Requirements
- At least 5 years of professional experience in backend engineering, ideally in a SaaS environment.
- Strong proficiency in Python and experience building production-ready backend applications and services.
- Experience designing, developing, and integrating REST APIs.
- Experience connecting third-party services within SaaS platforms.
- Familiarity with Large Language Models (LLMs) and AI-powered development tools.
- Familiarity with frameworks such as LangChain, Vercel AI SDK, and MCP servers.
- Experience working alongside Python-based AI services and connecting different technology stacks and systems.
- Understanding of scalable backend architectures, service integrations, and reliable production environments.
- Knowledge of AI integration patterns, LLM orchestration, and practical implementation of AI-powered product features is an advantage.
- Familiarity with PHP and/or Golang is a plus.
- Must be physically based within Europe or the Middle East and North Africa (MENA) region.
Responsibilities
- Design, develop, and maintain backend services that integrate AI capabilities into customer-facing product features.
- Build scalable, reliable APIs and backend systems that connect AI-generated outputs with existing SaaS functionality.
- Transform AI models, data, and services into practical solutions for property managers and guests.
- Collaborate with Product and Design teams on user experiences powered by artificial intelligence.
- Work with frontend engineers to connect backend AI services to application interfaces and deliver features.
- Partner with platform and integration engineering teams to embed AI capabilities into existing systems and customer workflows.
- Implement observability, monitoring, logging, and error handling for production AI services.
- Contribute to AI integration infrastructure, including Python SDKs, MCP servers, and LLM orchestration solutions.
- Optimize AI-powered workflows for smarter, faster, and more personalized customer interactions.
- Promote engineering best practices, maintainable architecture, and collaboration across technical and product teams.
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