Backend Developer

About the Company

GloPros is the all-in-one recruitment platform empowered by AI, delivering intelligent, scalable solutions for companies and talent. We build sophisticated, high-performance web experiences infused with AI to transform how organizations hire and how professionals advance their careers.

The GloPros Team

Join a dynamic, ambitious, and innovative team that values creativity, collaboration, and continuous learning. We foster a culture where your voice matters, and you'll work alongside professionals who are passionate about shaping the future of AI-powered hiring. Regular social events and daily team lunches make our office a welcoming place to connect, share ideas, and have fun.

About the Role

We’re seeking an experienced Backend AI Engineer to architect and build our Search Engine v2 powered by Weaviate and our intelligent HR integration platform. You’ll work directly with our CTO and Head of Product to bring breakthrough features to life, starting with our AI Recruitment Agent that reimagines the entire hiring workflow. This is a high-impact role where you’ll own significant technical initiatives from conception to production, directly shaping how thousands of users experience our platform daily.

Responsibilities

* Search Engine v2 (Weaviate-Powered)

* Architect Glopros's core search infrastructure using Weaviate as our vector database foundation

* Design and implement Hybrid Search leveraging Weaviate's native capabilities for superior semantic understanding

* Build multi-tenant search experiences tailored to three user personas: clients searching for candidates, candidates discovering opportunities, and recruiters managing pipelines

* Develop intelligent re-ranking algorithms that consider user context, historical interactions, and real-time signals

* Create real-time indexing pipelines that process candidate profiles, job descriptions, interview feedback, and interaction data

* Optimize Weaviate schemas, collections, and query patterns for sub-second latency at scale

* Implement cross-referencing and graph-based retrieval to surface hidden candidate-opportunity matches

* AI Recruitment Agent and other AI features

* Build autonomous agent workflows using LangChain and LangGraph that handle candidate screening, scheduling, and follow-ups

* Design multi-agent systems that collaborate to move candidates through hiring stages intelligently

* Create conversational interfaces where the agent can interact naturally with candidates, hiring managers, and recruiters

* Develop decision-making logic that knows when to escalate to human recruiters vs. handle autonomously

* Integrate with communication channels (email, SMS, Slack) for seamless agent-human handoffs

* HR Integration Platform

* Architect bidirectional sync systems with major ATS platforms (Greenhouse, Workday, Lever, Ashby, HiBob, Personio, SAP HCIS)

* Build automated enrichment pipelines that extract structured insights from interviews, resumes, and performance conversations

* Design fault-tolerant integration frameworks ensuring data consistency across Glopros, client ATS systems, and Weaviate

* Implement idempotency patterns preventing data duplication during high-volume syncs

* Create real-time webhooks that keep all systems synchronized as hiring workflows progress

* Workflow Improvements Across User Types

* For Clients (Hiring Managers): Build intuitive candidate discovery tools, automated candidate ranking, and interview scheduling automation

* For Candidates: Create personalized job matching, application tracking, and intelligent career guidance features

* For Internal Recruiters: Develop pipeline management dashboards, AI-assisted candidate screening, and automated administrative task handling

Qualifications

* 7+ years building production-grade LLM applications and agentic systems

* AI-first coding with Claude, Cursor, and Windsurf

* Hands-on experience with Weaviate or similar vector databases in production environments

* Deep expertise in Python and modern AI frameworks (LangChain, LangGraph, OpenAI API)

* Proven experience architecting RAG systems and hybrid search implementations

* Strong understanding of vector embeddings, semantic search, and retrieval optimization

* Production experience with FastAPI, microservices architecture, and distributed systems

* Hands-on experience with AWS, Kubernetes, and Docker

* Track record of building fault-tolerant, scalable backend features handling real-time data

Required Skills

* Core AI/ML Stack:

* Vector Database: Weaviate (schema design, hybrid search, GraphQL queries, tenant isolation)

* LLM Frameworks: OpenAI API, Anthropic

* RAG & Retrieval: Embedding models, semantic search optimization, re-ranking strategies, RAGAS evaluation

* LLM Ops: Prompt engineering, agent evaluation, fine-tuning

* Backend & Infrastructure: Languages: Python (required), Frameworks: FastAPI, Django, Databases: PostgreSQL

* Cloud: AWS (Lambda, ECS, S3), Kubernetes, Docker

* DevOps: CI/CD (Gitlab Actions), monitoring (Sentry), logging (CloudWatch)

* Integration & APIs: REST APIs, webhooks, contract-first development (OpenAPI/Anthropic)

* Experience with ATS platforms (Greenhouse, Workday, Lever, HiBob, Personio) is a major plus

* Real-time synchronization patterns and idempotency handling

Preferred Skills

* Previous experience in recruitment tech, HR tech, or marketplace platforms

* Understanding of multi-tenant SaaS architecture and data isolation patterns

* Knowledge of information retrieval theory and learning-to-rank algorithms

* Experience building conversational AI agents or chatbots

* Familiarity with data privacy regulations (GDPR, ISO compliance)

* Contributions to Weaviate or related open-source projects