Senior Full-Stack AI Engineer
New
I
Inallmedia.comRecruitment technology
100% remote from anywhere in Latin America, CET — minimum 6 hours of daily overlap with Netherlands business hours; 6 out of 8 hours per day with CET / CEST business hoursContractSenior
Salary not disclosed
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Job Details
- Languages
- Professional working proficiency in both Dutch and English
- Experience
- 5+ years of production software engineering experience
- Required Skills
- PythonRESTful APIsPrompt Engineering
Requirements
- Have 5+ years of production software engineering experience.
- Demonstrate independent technical design leadership and cross-system architecture experience.
- Bring advanced proficiency in Python.
- Have hands-on experience with backend microservices and RESTful API design.
- Have experience building and maintaining modern frontend web layers integrated with scalable backend services.
- Have a proven track record building production-grade LLM applications and agentic workflows.
- Be able to iterate system prompts, instrument evaluation metrics, and establish security and quality guardrails.
- Be comfortable presenting solutions to external clients and explaining technical constraints to business stakeholders.
- Have professional working proficiency in Dutch and English.
- Be able to operate within AWS WorkSpaces and provide a screenshot showing a passing AWS WorkSpaces health test during the interview process.
- Maintain at least 6 hours of daily overlap with Netherlands business hours.
Responsibilities
- Lead end-to-end technical design and execution across distributed systems, breaking roadmaps into testable incremental releases.
- Implement and optimize LLM agent behaviors for recruitment workflows using prompt iteration, evaluation harnesses, and output guardrails.
- Build, maintain, and scale responsive web applications, backend services, and external APIs.
- Design and deploy integrations with third-party software, including ATS platforms and CRM systems such as Salesforce.
- Work directly with staffing agency clients, non-technical partners, and engineering counterparts to identify operational bottlenecks and define technical specifications.
- Prototype AI-driven user experiences and gather early user feedback to validate technical feasibility.
- Improve platform resilience through code reviews, automated testing, production performance monitoring, and architecture simplification.
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