Applied AI Engineer (AI Agents & Workflow Automation)

TL;DR

Applied AI Engineer (AI Agents & Workflow Automation): Design, build, and maintain AI-driven services and agent-based solutions for workflow and business process automation with an accent on LLM-powered orchestration, RAG, tool calling, and integrations with business systems. Focus on developing production-grade backend components, ensuring reliability, scalability, and partnering across product lifecycle from discovery to iteration.

Location: Barcelona, Spain (hybrid onboarding starting remote with relocation support)

Company

Leading Chat Marketing platform used by 1.5M customers worldwide, helping creators boost engagement and sales via Instagram automations and channels like Messenger, WhatsApp, TikTok.

What you will do

• Design and build AI-driven services and agent-based solutions for workflow automation.
• Develop orchestration logic across LLMs, internal services, APIs, databases, and third-party platforms.
• Build backend components using TypeScript and Node.js for AI products and pipelines.
• Integrate AI workflows with CRM, ERP, ticketing, and other business systems.
• Implement RAG, tool calling, memory handling, evaluation, and monitoring for AI use cases.
• Partner with Product Managers and stakeholders to identify use cases and deliver solutions.
• Contribute across full product lifecycle with focus on testing, observability, and documentation.

Requirements

• 3–5 years in software/backend/applied AI engineering
• Strong TypeScript and Node.js in production
• Backend services, APIs, integrations experience
• LLM apps, AI automation, agentic workflows
• RAG, prompt engineering, tool calling, context management
• SQL/NoSQL databases, external APIs
• Reliable patterns: async, retries, queues, idempotency
• Business workflow understanding and stakeholder collaboration
• Strong communication for technical/non-technical audiences

Nice to have

• LangChain, LangGraph, OpenAI SDK, LlamaIndex
• n8n, Temporal, event-driven systems
• PostgreSQL, Redis, Kafka, BullMQ
• Vector DBs: pgvector, Pinecone, Qdrant
• Python for AI/ML
• Docker, AWS/GCP/Azure, CI/CD
• AI observability and evaluation tools
• AI security, privacy, governance

Culture & Benefits

• Hybrid work with generous leave for work-life balance
• Comprehensive health insurance for you and family
• Professional development budget for courses and conferences
• Flexible benefits package tailored to your needs
• In-office perks: free meals, snacks
• Company-funded sports, offsites, team-building