Top Tech Jobs & Startup Jobs in Madrid

Own and grow a large agricultural enterprise territory, generating pipeline through relationships, outbound prospecting, events, and field demonstrations. Lead the full sales cycle from discovery and ROI development through negotiation, closing, and account expansion. Build relationships with growers, agronomists, executives, and technical stakeholders; maintain forecasts and CRM accuracy; support pricing and market positioning; and coordinate customer handoffs and deployments.

As a Distributed Systems Engineer, you'll design and evolve LiveKit's core systems, implement resilient architectures, and enhance reliability and developer velocity, working on critical features in production environments.

Build post-training infrastructure for voice and text agents, including training environments, verifiers, synthetic data pipelines, evaluations, and model release gates. Run end-to-end training experiments, select open-weight models, improve tool-using and multi-turn behavior, deploy models to production, and iterate using real-world usage. The role emphasizes Python engineering, reinforcement learning, GPU-based training, data quality, reward design, and production machine learning.

Lead the company’s ML/AI platform from experimentation through production, including SageMaker training infrastructure, model serving, inference pipelines, MLOps, and Java microservice integrations. Set AI/ML technical direction, develop GenAI and LLM retrieval and agent architectures, establish evaluation and safety guardrails, and partner with data science, DevOps, product, and engineering leadership on scalable ML roadmaps.

Design and implement scalable backend services and APIs with tight AI/LLM integration. Collaborate with product and data science teams to operationalize models, deploy microservices (Docker/Kubernetes), maintain CI/CD and reliability, mentor junior engineers, drive technical best practices, ensure security and compliance, and lead feature development and documentation.

This is a spontaneous application opportunity for candidates to express interest in future roles within the company, not currently hiring for any specific position.

Deploy enterprise-grade AI solutions, focusing on RAG pipelines and LLM workflows, while optimizing solutions on the Stack AI platform for strategic accounts.

Brainly invites interested candidates to submit their CV and skills for potential future openings as the company continues to grow and adapt quickly.

The Senior Infrastructure Engineer will own the cloud stack, enhance observability, architect browser cloud infrastructure, debug operational issues, and mentor other engineers, while managing multiple production workloads at scale.

Design and maintain data warehouse systems, develop ETL pipelines, manage datasets for analytics, and implement real-time data solutions.