
51 - 200 employees
Founded 2016
🤖 Artificial Intelligence
🛍️ eCommerce
Artificial Intelligence • Robotics • eCommerce
Gugu Robotics is a pioneering startup based in West Africa, dedicated to harnessing the power of AI, robotics, and drone technology to create innovative solutions for various industries. Founded by visionary engineer Emmy Pencil, the company specializes in designing and building customized robotic systems, drones, and AI-enabled electric vehicles that address critical challenges across sectors such as agriculture, military, medical, and beyond. With a diverse team of experts, Gugu Robotics aims to redefine possibilities in automation and efficient energy solutions to shape the future of technology.
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51 - 200 employees
Founded 2016
🤖 Artificial Intelligence
🛍️ eCommerce
Artificial Intelligence • Robotics • eCommerce
Gugu Robotics is a pioneering startup based in West Africa, dedicated to harnessing the power of AI, robotics, and drone technology to create innovative solutions for various industries. Founded by visionary engineer Emmy Pencil, the company specializes in designing and building customized robotic systems, drones, and AI-enabled electric vehicles that address critical challenges across sectors such as agriculture, military, medical, and beyond. With a diverse team of experts, Gugu Robotics aims to redefine possibilities in automation and efficient energy solutions to shape the future of technology.
• Define AI architecture and technical strategy, and lead implementation across the full lifecycle from design through production • Build scalable ML platforms, pipelines, and workflow orchestration that support model development and event-driven, asynchronous operations at scale • Architect and build LLM-powered systems, including prompt engineering, function/tool calling, multi-agent orchestration, RAG patterns, vector databases, embeddings, and streaming responses • Design and develop APIs and backend services that integrate AI capabilities with enterprise systems and third-party platforms • Lead model development, optimization, and the path from research to production, ensuring promising approaches translate into reliable, production-ready systems • Ensure AI reliability, security, and scalability across deployed systems, including logging, monitoring, and debugging in production environments • Bring an AI-forward mindset to your daily work, using tools like Claude, Cursor, and other modern AI assistants to ship higher-quality work at pace • Co-define the AI roadmap with leadership, operating as a peer in strategic technical conversations • Communicate complex technical concepts clearly to engineering and non-engineering stakeholders alike, translating depth into decisions others can act on • Engage with product, engineering, and data teams to align AI work with broader business priorities • Define and champion AI engineering standards that shape how the organization builds and operates AI systems • Mentor across the organization, shaping engineering culture and developing the next generation of technical leaders • Own high-stakes architectural decisions that carry significant organizational and cross-engagement weight • Drive technical vision — defining not just what gets built, but how AI engineering evolves at R&P over time
• 7+ years of experience in AI/ML engineering • Strong proficiency in Python • Strong software engineering background, including system design, API design, code quality, and strong unit testing practices • Experience designing and working with distributed systems and event-driven architectures • Expertise in MLOps and AI infrastructure, including model versioning, monitoring, deployment automation, and reproducibility • Experience with Amazon Quick, ServiceNow integration, Jira integration, AWS Bedrock, Agentic AI/ML (prompt engineering, agent development), Natural language querying / analytics • Strong stakeholder communication skills, with the ability to translate technical depth across audiences • In-depth experience with AWS, especially AWS GenAI offering; working knowledge of other cloud platforms • Familiarity with both SQL and NoSQL databases, including scalable design patterns • Experience with workflow orchestration tools and asynchronous system operations • Hands-on experience with LLM systems, including prompt engineering, function/tool calling, multi-agent orchestration, RAG architectures, vector databases, embeddings, and streaming LLM responses • Experience with containerization (e.g., Docker) and cloud-native AI architecture patterns • Exposure to AI governance and compliance considerations in production environments
• Health insurance • 401(k) matching • Flexible working hours • Paid time off • Remote work options
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