AI Engineer (Agentic Systems)
Design and build production-grade AI systems, with a focus on agentic architectures, scalable machine learning, model evaluation, and turning emerging research into working prototypes.
At Bose Corporation, we believe sound is the most powerful force on earth — and for over 60 years, we have been a company built on innovation, excellence, and independence. Privately owned, fiercely customer-focused, and driven by our values, we continue to lead industries and transform lives through sound.
Today, Bose Corporation is entering an exciting new era. Across multiple global Business Units and Global Functions, we are shaping the future of audio technology, automotive, luxury, and premium experiences. We invite you to join us in this transformation.
Build AI that people can hear and experience.
At Bose, we believe sound is the most powerful force on earth. As a Machine Learning / AI Engineer, you’ll help bring that belief to life - developing intelligent capabilities for the next generation of audio experiences.
If you enjoy experimenting with models, solving practical problems, and turning ideas into working technology, this is an opportunity to grow your skills while contributing to products and technology that people use every day.
About the Role
You’ll help design, train, test, and optimize machine learning models, with a focus on making AI work efficiently on devices with limited memory and computing power. This work brings together Efficient AI and Edge ML: building models that deliver strong results within the constraints of real products.
You’ll collaborate with engineers across machine learning, software, embedded systems, and hardware. Along the way, you’ll deepen your technical expertise, contribute your ideas, and learn how models move from experimentation toward deployment.
What You’ll Do
What You’ll Bring
Experience That Can Help You Stand Out
You don’t need experience in every area below. We’re interested in the strengths you bring and what you’re excited to learn.
Design and build production-grade AI systems, with a focus on agentic architectures, scalable machine learning, model evaluation, and turning emerging research into working prototypes.
Build and operate AI evaluation pipelines, backend services, and cloud infrastructure, turning research prototypes into reliable production workflows while tracking model quality, performance, and cost.
Design and oversee LLM and intelligent-agent architectures, implement multi-agent workflows, and collaborate across product, UX, data, backend, and MLOps teams to deliver business solutions.
Design and implement intelligent manufacturing technologies and AI-enabled production solutions, while managing R&D project delivery, technical documentation, and collaboration with engineering teams.
Build autonomous AI agents for executive workflows and develop evaluation systems that measure their reliability, detect failures, and verify improvements before changes reach users.