Lead Software Engineer, Ai & Data

lead software engineer, AI & data BRAVO CAPITAL · Valencia · full-time · on-site, five days a week very competitive salary you enjoy hard problems, go deep to understand how things work and explain complex ideas simply you’ll lead software, data, AI and infrastructure, setting technical direction, building useful systems and leading our four-person Analytics team what you’ll dobuild agents and apps with frontier AI models, choosing the best balance of capability, speed and costbuild reliable data pipelines and apply statistics and machine learning to real business problemsown delivery from code to production, including Git Hub CI/CD pipelines, cloud infrastructure and resilient systemswork directly with business teams, explain trade-offs clearly and help others build better what we’re looking for3+ years of professional experience in software, data or applied AI, with Git Hub projects you can explain in deptha degree in data science, computer science or computer engineeringstrong analytical thinking, curiosity, attention to detail and the initiative to solve problems independentlyexcellent communication: clear writing, careful listening and simple explanations for technical and nontechnical colleaguespractical knowledge of Git Hub, CI/CD, AWS, S3, Hetzner and Dev Ops, including testing, security, monitoring, backups and recovery tools you’ll work with Go, Rust, Python, SQL, React, Type Script, Postgre SQL, SQL Server, Docker and Linux AI coding tools such as Codex, Claude Code and Cursor, plus MCP, skills, prompts, context, caching, RAG and evaluations you don’t need every tool on day one, but you should learn quickly and test what you build we value strong algorithms and systems fundamentals, deep optimisation and model training or fine-tuning, with resources available when the problem calls for them apply with your CV, Git Hub and two projects, explaining what you built and one technical decision share only work you’re authorised to disclose and confirm you can work in our Valencia office five days a week

work directly with business teams, explain trade-offs clearly and help others build better what we’re looking for 3+ years of professional experience in software, data or applied AI, with Git Hub projects you can explain in depth a degree in data science, computer science or computer engineering strong analytical thinking, curiosity, attention to detail and the initiative to solve problems independently excellent communication: clear writing, careful listening and simple explanations for technical and nontechnical colleagues practical knowledge of Git Hub, CI/CD, AWS, S3, Hetzner and Dev Ops, including testing, security, monitoring, backups and recovery tools you’ll work with Go, Rust, Python, SQL, React, Type Script, Postgre SQL, SQL Server, Docker and Linux AI coding tools such as Codex, Claude Code and Cursor, plus MCP, skills, prompts, context, caching, RAG and evaluations you don’t need every tool on day one, but you should learn quickly and test what you build we value strong algorithms and systems fundamentals, deep optimisation and model training or fine-tuning, with resources available when the problem calls for them apply with your CV, Git Hub and two projects, explaining what you built and one technical decision share only work you’re authorised to disclose and confirm you can work in our Valencia office five days a week

lead software engineer, AI & data BRAVO CAPITAL · Valencia · full-time · on-site, five days a week very competitive salary you enjoy hard problems, go deep to understand how things work and explain complex ideas simply you’ll lead software, data, AI and infrastructure, setting technical direction, building useful systems and leading our four-person Analytics team what you’ll do build agents and apps with frontier AI models, choosing the best balance of capability, speed and cost build reliable data pipelines and apply statistics and machine learning to real business problems own delivery from code to production, including Git Hub CI/CD pipelines, cloud infrastructure and resilient systems