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Napster is building embodied, multimodal AI agents designed to work alongside people in their existing workflows—through video presence, voice, and text. The company democratizes access to AI expertise, enabling employees and customers to leverage institutional knowledge across their organizations.
You will join the Partnerships & Ecosystems team as a Forward Deployed Engineer embedded within the Commercial Enablement motion. This is a hands-on builder role focused on creating the technical tools, demos, and experiences that enable Napster's sellers and partners to confidently demonstrate, prototype, and deploy AI solutions.
Key Responsibilities:
- Build reusable, high-impact demos showcasing Napster's voice, real-time video, and embodied AI capabilities; translate customer and partner scenarios into configurable experiences with clear setup instructions and guidance.
- Create evaluation environments and hands-on build experiences where sellers and partners can explore products, test ideas, and build prototypes with starter projects, sample data, and guided exercises.
- Engineer agent-led enablement tools such as interactive asset portals, guided solution discovery, and demo-building assistants using Napster's own technology.
- Develop and deliver practical AI-building programs including workshops, build-alongs, and partner co-creation sessions that teach people to combine existing applications with Napster solutions, adapted for different technical skill levels.
- Build reusable technical components: integrations, agent tools, MCP servers, knowledge and memory layers, custom front ends, and orchestration patterns that support repeatable use cases.
- Enable Napster Innovation Hub experiences by building and validating interactive experiences for partner events and innovation hubs, packaged with configuration guidance and troubleshooting instructions.
- Support selected partner prototypes and reference deployments by scoping integrations, establishing success criteria, and validating high-value use cases; turn successful work into reusable reference implementations.
- Build quality and responsible use into every experience through testing agent behavior, tool use, conversation quality, latency, and failure handling; apply appropriate access controls, data handling, and safety guardrails.
- Drive adoption by observing how sellers and partners use tools, identifying friction points, and improving experiences; feed gaps back to Product and Engineering.
You will report to Technology Partner Management with functional alignment to Commercial Enablement & Partner Experience, working day-to-day with the Commercial Enablement team.
Development Approach:
You'll use agentic coding tools such as Claude Code, Cursor, Lovable, and Codex alongside Napster's own solutions to scope, prototype, and iterate quickly. The team embraces AI-assisted development while maintaining strong engineering judgment, testing behavior, protecting data, and ensuring solutions are maintainable. Every successful build should be packaged into reusable templates, agent skills, integrations, and reference implementations.
Success Metrics:
- Sellers can run compelling demos with confidence.
- Partners can use starter kits to build their own prototypes.
- Agent-led tools make onboarding and resource discovery easier.
- Innovation Hub experiences are reliable and repeatable.
- Tools and programs enable more people to succeed with Napster without proportional growth in engineering headcount.
Requirements:
- 10+ years of hands-on software engineering experience. You can build and debug working applications, connect APIs, manage authentication, and deploy maintainable solutions across front-end, backend, and cloud environments.
- Practical experience building with AI: you have created agentic applications or AI-enabled workflows and can explain decisions around models, tools, context, retrieval, memory, and evaluation. Experience with real-time voice, video, or multimodal applications is valuable.
- AI-native development workflow: you use AI coding tools to accelerate real work while remaining accountable for output quality. You can inspect, challenge, test, and improve AI-generated code—not just generate prototypes.
- Ability to build with people, not just for them. You are comfortable running hands-on sessions, explaining technical concepts clearly, and helping partners work through problems. You know when to demonstrate, co-build, or equip someone to continue independently.
- Product mindset and strong ownership. You think about usability, reuse, documentation, and adoption. You can take ambiguous requests, define practical first versions, and iterate based on feedback.
