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.