Principal AI Software Engineer

Join our team as a Principal AI Software Engineer, where you will define and drive the engineering vision across multiple teams, mentor and develop engineers, shape the engineering culture, and partner with executives to co-create technical strategy. You will lead high-ambiguity technical initiatives, identify and resolve systemic technical issues, establish standards for AI system quality, and champion engineering excellence. This role requires extensive experience in Python, language model-based solutions, AI/ML tooling, security and compliance requirements, and cloud-native infrastructure.

• Definir y dirigir la visión de ingeniería a través de múltiples equipos, alineando la dirección tecnológica con los objetivos comerciales de la empresa.
• Mentorizar y desarrollar a los ingenieros a través de coaching estructurado, patrocinio arquitectónico e inversión deliberada en su crecimiento como tomadores de decisiones técnicas.
• Establecer estándares compartidos, elevar el nivel técnico en la contratación e influir en cómo se desarrolla la competencia en ingeniería en todos los niveles.
• 6+ years of experience with Python in production environments, with a track record of building systems that have scaled across organizations
• 3+ years of experience designing, deploying, and operating language model–based solutions at production scale, including demonstrated ownership of LLM system reliability, evaluation, and iteration strategy
• Recognized expertise in the AI/ML tooling ecosystem — including agentic frameworks, MCP, A2A protocols, and the evolving GenAI infrastructure landscape with a history of translating emerging technology into production grade capabilities
• Proven ability to build systems that are simultaneously innovative, reliable, maintainable, and aligned with long-term business needs — with the judgment to know when to move fast and when to invest in foundations
• Deep, hands-on fluency with AI coding assistants (GitHub Copilot, Cursor, Claude Code) as a core part of engineering workflow, and a demonstrated ability to shape team-wide adoption and best practices around these tools
• Expert-level understanding of security, privacy, and compliance requirements in AI-enabled enterprise systems
• Demonstrated ability to diagnose, communicate, and permanently resolve high-severity production issues involving complex AI systems
• Extensive experience with container orchestration and cloud-native infrastructure in production, including ownership of platform-level decisions that affect multiple teams
• Mastery of software engineering fundamentals — architecture patterns, CI/CD, testing strategy, observability, and code quality — and a demonstrated record of establishing these standards at the organizational level
• Recognized internally — and ideally externally — as a credible technical voice, someone whose perspective shapes how the organization thinks about hard problems
• Ability to synthesize ambiguity into a coherent technical vision, align diverse stakeholders around it, and sustain that alignment over time
• A track record of driving major technical decisions and organizational change through influence rather than authority, including across teams and domains outside your direct scope
• Exceptional ability to communicate across the full organizational stack — from detailed technical design with engineers to strategic framing with executives — calibrating depth and abstraction with precision