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GloPros

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Backend Developer

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Summary

Build and scale the Python/Django backend of GloPros' AI-powered recruitment platform: REST APIs, PostgreSQL data modeling, Celery/Redis background jobs, third-party integrations, and AWS/Terraform infrastructure, with roughly 20-25% of time on agentic LLM features like matching and outreach. Amsterdam-based hybrid role (four office days, one remote).

GloPros is a Recruitment & Consulting company, powered by an AI-platform. We deliver global professionals across every industry, high-skilled and available as permanent hires, freelancers or consultants. You'll join a team that values professionalism, integrity, and continuous improvement.

As part of our tech team, you will build and strengthen the backend systems that power the platform: business-critical APIs, data workflows, third-party integrations, search, and selected agentic AI features used by recruiters and candidates.

About the Role

We are looking for a hands-on Backend Developer who enjoys turning product requirements into reliable, maintainable software. Your primary focus will be our Python/Django backend: designing APIs, modelling domains and data, improving performance, and raising engineering quality across the codebase.

Agentic AI is an important part of our roadmap, but this is not a pure AI or ML role. You will integrate LLMs and retrieval components where they solve a real user problem, and you may build or improve agents for matching, outreach, enrichment, and workflow automation. We expect the role to be approximately 75-80% backend/platform engineering and 20-25% agentic AI work.

What You’ll Do

  • Develop, maintain, and scale backend services in Python and Django, including REST APIs, domain logic, data models, and background jobs.
  • Design clear API contracts and collaborate with frontend developers and product stakeholders from discovery through production rollout.
  • Model and optimize data in PostgreSQL; improve query performance, indexing, transactions, and data integrity.
  • Build reliable asynchronous workflows using Celery and Redis, with appropriate retries, idempotency, and observability.
  • Integrate external platforms and APIs, including ATS, HR, sourcing, and recruitment systems, with robust error handling and monitoring.
  • Improve backend architecture incrementally, separating business logic from views and serializers and establishing clear service, selector, and domain boundaries.
  • Write automated tests, review code, investigate production issues, and improve CI/CD practices so the team can ship safely and frequently.
  • Contribute to AWS infrastructure and Terraform-managed environments together with the wider engineering team.
  • Build and productionize selected agentic AI capabilities, such as candidate enrichment, matching explanations, outreach drafting, or workflow automation.
  • Integrate LLM APIs and search/retrieval components with attention to latency, cost, privacy, evaluation, fallbacks, and operational reliability.
  • Use AI-assisted engineering tools pragmatically for code review, testing, documentation, and codebase navigation.

What We’re Looking For

  • 3-7 years of professional backend development experience, with strong production experience in Python.
  • Hands-on experience with Django and Django REST Framework, or comparable experience and a willingness to work deeply in Django.
  • Strong understanding of REST API design, authentication and authorization, background processing, and integration patterns.
  • Solid PostgreSQL knowledge, including relational modelling, migrations, indexing, and query optimization.
  • Experience writing clean, testable code and working with automated tests, code review, Git, Docker, and CI/CD.
  • Experience deploying or operating services in AWS and familiarity with infrastructure as code, preferably Terraform.
  • A practical product mindset: you clarify requirements, make sensible trade-offs, and take ownership from implementation through production support.
  • Clear communication and a collaborative approach to working with backend, frontend, product, and other stakeholders.
  • Interest in agentic AI and LLM-powered product features; production experience is valuable, but deep ML research experience is not required.

Bonus Points

  • Experience with OpenSearch, Weaviate, FAISS, Pinecone, or another search/vector database.
  • Experience with retrieval-augmented generation, hybrid search, embeddings, or LLM evaluation.
  • Familiarity with LangChain, LlamaIndex, or a comparable orchestration framework.
  • Experience building AI agents, tool-calling workflows, voice agents, or human-in-the-loop automation.
  • Experience with high-volume webhooks, third-party integrations, or recruitment/HR technology.
  • Familiarity with domain-driven design or an opinionated Django service/selector architecture.
  • Experience improving observability, application security, or performance in a production SaaS platform.

How We Work

  • Backend reliability and maintainability come first; AI is used where it creates measurable product value.
  • We make architectural improvements incrementally while continuing to deliver customer-facing features.
  • Technical decisions and important agreements are documented so the team can work with shared context.
  • New standards are proposed, discussed, and adopted collaboratively.
  • Engineers are encouraged to bring ideas, challenge assumptions, and own outcomes—not only tickets.

What Success Looks Like

  • You ship dependable backend features that are easy for others to understand, test, and extend.
  • You improve API quality, database performance, background processing, and production visibility in the areas you touch.
  • You help reduce architectural friction and move business logic toward clearer, well-tested boundaries.
  • You contribute agentic features that are evaluated, monitored, cost-conscious, and useful in real recruitment workflows.
  • You raise team quality through thoughtful code reviews, documentation, and constructive technical collaboration.
  • Amsterdam-based hybrid working: four days in the office and one day remote.
  • Competitive salary and ESOP participation.
  • Annual learning and development budget.
  • Access to modern AI tooling and infrastructure.
  • Regular team offsite, collaborative engineering culture.

Skills

See also

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