Senior Software Engineer (Placer Intelligence)

Join our team as a Senior Software Engineer specializing in Placer Intelligence. In this fully remote role, you will lead the development of our AI-powered location intelligence platform, overseeing full-stack development and making key architecture decisions. You will work closely with product, design, and customers, turning vague requirements into clear technical plans and building production-ready solutions. Ideal candidates have 10+ years of software engineering experience, a strong understanding of AI, and a passion for building scalable platforms.

• Conduire la vision technique et l'architecture de la plateforme d'intelligence de localisation alimentée par l'IA, en construisant des solutions prêtes pour la production.
• Superviser le développement full-stack de notre système d'IA conversationnelle, de l'intégration des LLM aux interfaces de streaming en temps réel.
• Collaborer étroitement avec les équipes produit, design et clients pour transformer des exigences vagues en plans techniques clairs.

• If you are a technical leader with 10+ years of software development experience, proven success in production GenAI environments, and a passion for building scalable AI platforms that deliver measurable business impact, we want to hear from you
• High EQ: you listen well, read what stakeholders really need, and can disagree while keeping trust
• 10+ years of software engineering, shipping customer-facing products in production
• Clear communicator with both technical and non-technical people
• Comfortable with ambiguity: you work independently and know when to ask for help
• Strong full-stack fundamentals: Python (FastAPI or similar), React and TypeScript, relational databases and SQL, and shipping containerized services to the cloud
• An AI-native workflow: you plan before prompting, work in small reviewable steps, give your agents good context, use tests as the safety net, and can tell when their output is wrong
• Hands-on experience shipping LLM-powered features: context engineering (prompts, retrieval, tools, memory), evals, handling model failures, and AI system architecture
• Strong product sense: you understand the user's problem, care about the experience, and push back when something doesn't feel right
• Strong system design: data modeling, API design, and production systems that stay reliable, fast, and secure as they grow. You can explain the trade-offs behind your choices
• Demonstrated use of AI tools to work more efficiently—whether professionally or personally—and a curiosity for finding new ways to apply them
• Comfort integrating generative AI into day-to-day workflows to boost productivity, quality, and output