Start Date: general timeframe (or earlier)
Location: Hybrid — Country-centre office (4 days onsite / 1 day remote)

About the Company
We are an AI-driven, end-to-end recruitment platform that delivers intelligent, scalable hiring solutions for organizations and job seekers. Our product combines high-performance web experiences with AI to streamline hiring workflows and help professionals advance their careers.

Team and culture
Join a fast-moving, collaborative team that values creativity, learning, and impact. Our culture encourages open contribution, cross-functional collaboration, and regular team events that make the office an energizing place to work.

Role overview
We are hiring an experienced Full Stack AI Engineer to lead the architecture and implementation of Search Engine v2 (Weaviate-powered) and our HR integration platform. You will work closely with senior leadership to deliver high-impact features, beginning with an AI Recruitment Agent that reimagines the hiring workflow. This role owns technical initiatives end-to-end and will shape how thousands of users experience the platform.

Key responsibilities
- Architect and implement the core search infrastructure using Weaviate as the vector database foundation.
- Design and deliver hybrid search capabilities leveraging Weaviate for robust semantic understanding.
- Build multi-tenant search experiences for client recruiters, candidates, and hiring managers.
- Develop intelligent re-ranking and personalization algorithms incorporating context, interaction history, and real-time signals.
- Create real-time indexing pipelines for candidate profiles, job descriptions, interview feedback, and interaction data.
- Optimize schemas, collections, and query patterns for sub-second latency at scale.
- Implement cross-referencing and graph-based retrieval to surface latent candidate-job matches.
- Build autonomous agent workflows (LangChain, LangGraph) for screening, scheduling, and follow-ups.
- Design multi-agent systems and conversational interfaces that interact naturally with candidates, hiring managers, and recruiters.
- Implement decision logic for agent escalation vs. autonomous handling and integrate agent workflows with email, SMS, and chat tools.
- Architect bidirectional syncs with major ATS platforms and build fault-tolerant enrichment pipelines to extract structured insights from resumes, interviews, and performance data.
- Ensure data consistency with idempotent sync patterns and real-time webhooks.
- Deliver user-facing improvements across personas: candidate discovery and ranking, personalized job matching, application tracking, pipeline dashboards, and AI-assisted screening.

Required experience and skills
- 7+ years building production-grade LLM applications and agentic systems.
- Practical experience with Claude, Cursor, or similar AI-first coding workflows.
- Hands-on production experience with Weaviate or comparable vector databases.
- Strong Python expertise and experience with modern AI frameworks (LangChain, LangGraph, OpenAI API).
- Proven experience designing RAG systems and hybrid search implementations.
- Deep understanding of vector embeddings, semantic search, and retrieval optimization.
- Production experience with FastAPI, microservices, and distributed systems.
- Familiarity with AWS, Kubernetes, Docker, and deploying fault-tolerant real-time systems.
- Track record of building scalable backend features that handle high-throughput syncing and indexing.
- Experience with REST APIs, webhooks, and contract-first API design.

Technical stack highlights
- Vector DB: Weaviate (schema design, hybrid search, tenant isolation)
- LLMs & APIs: OpenAI, Anthropic
- Retrieval: Embeddings, re-ranking strategies, RAG patterns
- Frameworks: FastAPI, Django (where applicable)
- Databases: PostgreSQL
- Cloud & Orchestration: AWS (Lambda, ECS, S3), Kubernetes, Docker
- DevOps & Observability: CI/CD (GitLab), monitoring (Sentry), logging (CloudWatch)
- ATS integrations: experience with platforms such as Company, Company, Company, Company, Company is a plus

Nice-to-have
- Prior experience in recruitment or HR tech, marketplaces, or multi-tenant SaaS.
- Familiarity with information retrieval theory, learning-to-rank methods, and conversational AI.
- Knowledge of data privacy and compliance frameworks (GDPR, ISO).
- Contributions to Weaviate or related open-source projects.

Collaboration and reporting
You will collaborate closely with:
- CTO: align on architecture, scaling, and engineering roadmap
- Backend engineers: co-design systems and implement features
- Product: translate product vision into technical requirements and prioritization
- Data leadership: co-own search and data architecture
- Cross-functional teams: designers, recruiters, and sales to ensure solutions meet user needs

Why this role matters
This position offers the opportunity to lead architecturally significant work that directly impacts user experience and the product’s AI capabilities. You will deliver systems that speed hiring, improve matching quality, and automate repetitive tasks so teams can focus on high-value work.

If you’re an experienced AI-first engineer excited to build scalable search, autonomous agent workflows, and robust integrations for a fast-growing recruitment platform, we’d love to hear from you.

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Semantics

Algorithms

Indexing

Collections

LangChain

Scheduling

Multi-Agent Systems

Communication

Sync (Unix)

SAP CRM

Data Consistency

Webhooks

Automation

Database Cursor

Python (Programming Language)

Application Programming Interface (API)

Semantic Search

Microservices

Amazon Web Services

GraphQL

Prompt Engineering

FastAPI

DevOps

OpenAPI

Conversational AI

ISO Compliance

Data Architecture

Scale (Map)

Observability

M (Programming Language)

Data Synchronization

Django (Web Framework)

Embedding

Gitlab

Logging (Construction)

Docker (Software)

Amazon S3

AWS Lambda

Kubernetes

Information Retrieval

Full Stack Engineer

Full Stack Engineer

Contract Details

Work Location

Company Information

Multinational Company

Food and Beverage Manufacturing

5001-10.000 employees

Multinational Company

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