Senior / Staff Software Engineer, AI Engineering

Suno Suno · Multimodal · Boston, MA · Engineering

Senior/Staff Software Engineer, AI Engineering role at Suno, focused on building and owning AI-powered internal systems to support non-engineering functions. The role involves designing, building, and maintaining infrastructure for these systems, embedding with cross-functional partners, and expanding AI-enabled tooling. Requires hands-on experience with LLMs and agentic workflows, and shipping internal tooling.

What you'd actually do

  1. Design and build AI-powered internal systems for a range of functions across Suno
  2. Own the underlying infrastructure that keeps those systems running in production — reliable, observable, and easy to extend to new use cases
  3. Embed with cross-functional partners to understand their workflows, surface the right problems to solve, and prioritize what gets built next
  4. Partner with engineering teams to expand AI-enabled tooling and ensure our internal systems benefit from the company's broader AI infrastructure
  5. Help non-engineering teams move faster and with more capability, contributing to Suno's mission of making creative fulfillment a daily reality for everyone

Skills

Required

  • 5-7+ years of full-stack software engineering experience
  • Demonstrated experience building and shipping internal tooling or systems that support business functions
  • Hands-on familiarity with the current landscape of AI for software engineering, including LLMs, AI APIs, and agentic workflows
  • Strong communicator who can work effectively with non-engineering partners

Nice to have

  • Experience on a platform, developer experience, or enterprise engineering team where internal teams were your primary customers
  • Familiarity with support tooling, CRM systems, or workflow automation platforms
  • Experience standing up observability and operational practices for internal systems from scratch
  • Comfort operating in an early-stage, 0→1 environment where the problem space is still being defined

What the JD emphasized

  • building and shipping internal tooling or systems that support business functions
  • Hands-on familiarity with the current landscape of AI for software engineering, including LLMs, AI APIs, and agentic workflows - you've actually built and shipped something with these tools, not just used AI as a coding assistant

Other signals

  • AI-powered internal systems
  • 0->1 role
  • own the underlying infrastructure