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# Ai Engineer

- **Company:** Wave Group
- **Location:** Madrid, Spain
- **Salary:** €100,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Cloud Computing, Code Review, Computer Programming, Continuous Integration, Python (Programming Language), Redis, Regression Testing, Service Design, Test Data, Twilio, Data Logging, Real Time Systems, ReactJS, Large Language Models, Multi-Agent Systems, Backend, Git, Low Latency, Celery, Front End Software Development, Restful APIs, Docker
- **Published:** September 27, 2026
- **Apply:** https://www.buscojobs.com.es/ai-engineer-en-madrid-ID-373576091

## About the Role

Strong Python backend engineering - async programming, high-throughput/message-queue systems (Celery + Redis or equivalent), production-grade service design
Experience building evaluation pipelines for non-deterministic systems - accuracy/consistency testing, regression testing across prompt and model changes, synthetic test data generation
Production observability instincts - tracing, logging, metrics, alerting on failures and degraded performance, cost tracking and optimisation across model calls
Cloud deployment and containerisation experience (AWS/GCP, Docker)
Git, testing, CI/CD, code review - clean, testable, well-documented code as standard practice
Startup pace and mentality - high energy, ownership, proactiveness, hunger to innovate and succeed, comfortable operating with ambiguity
Conversational/voice AI experience - STT/TTS pipelines, turn-taking, telephony integration (e.g. Twilio), latency-sensitive real-time systems
Frontend experience (ideally React)
Experience building enterprise or B2B products
Model fine-tuning or model-selection/cost-optimisation experience
#J-*****-Ljbffr

## Description

BenefitsSalary: up to ~€100k (flex for strong candidates)+ up to 35% bonus (~20% standard, rest based on performance)Equity: very generous, early stage equity (~70% of your base)Location:Madrid (preferred) or Barcelona (1-2 office days)Company: autonomous AI agents for enterprise clientsAbout the companyThis rapidly scaling start-up is building an AI-native platform that lets enterprise clients run high-volume operations through autonomous, conversational agents - voice, chat and messaging, deployed across dozens of countries in over 60 languages, for some of the largest employers in the world.The company's core technical challenge is multi-agent orchestration that stays rock-solid at scale - reliable, secure and observable whether it's deployed for a healthcare provider in the US or a retailer in Latin America.Founded by an experienced team with two prior successful exits, backed by a top-tier European VC, and already trusted by household-name enterprise customers.About the roleYou'll build, operate and continuously improve the reliability of the agentic AI systems running in production for enterprise clients - focused on how agents behave, decide, fail, recover and scale under real operational load, not just on shipping new features.You'll own the observability and evaluation layer that keeps autonomous agents trustworthy at scale - tracing, logging, cost tracking across model calls, regression testing through prompt and model changes, and alerting on failures, hallucinations and degraded performance before customers ever see them.You'll also work end-to-end across the stack: production-grade async Python services, LLM/RAG pipelines, and the conversational voice layer where relevant - STT/TTS, telephony, real-time latency.Must have requirementsProfessional fluency inEnglish (and ideally Spanish)Strong Python backend engineering - async programming, high-throughput/message-queue systems (Celery + Redis or equivalent), production-grade service designExperience building evaluation pipelines for non-deterministic systems - accuracy/consistency testing, regression testing across prompt and model changes, synthetic test data generationProduction observability instincts - tracing, logging, metrics, alerting on failures and degraded performance, cost tracking and optimisation across model callsCloud deployment and containerisation experience (AWS/GCP, Docker)Git, testing, CI/CD, code review - clean, testable, well-documented code as standard practiceStartup pace and mentality - high energy, ownership, proactiveness, hunger to innovate and succeed, comfortable operating with ambiguityConversational/voice AI experience - STT/TTS pipelines, turn-taking, telephony integration (e.g. Twilio), latency-sensitive real-time systemsFrontend experience (ideally React)Experience building enterprise or B2B productsModel fine-tuning or model-selection/cost-optimisation experience#J-*****-Ljbffr


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