Staff Backend Software Engineer, Otter.ai

• Has 10+ years of experience building and scaling complex systems
• Has a strong track record of owning technical and product direction for large or ambiguous problem spaces
• Demonstrates deep expertise in system design, especially in data-intensive or distributed systems
• Has experience leading cross-team initiatives and influencing without direct authority
• Brings strong product intuition and can balance user experience, system constraints, and business impact
• Is comfortable operating at a high level of ambiguity and defining both the problem and the solution

Desirable

• As a Staff Software Engineer on our Product teams, you’ll define how these capabilities are translated into scalable systems and cohesive product experiences
• You’ll operate across the full lifecycle of AI-driven features—from data ingestion and model orchestration to output structuring and delivery into user-facing product surfaces—but at a systems level. This includes shaping the architecture behind generation pipelines, defining how AI outputs are structured and persisted, and ensuring these systems are reliable, performant, and adaptable as both product requirements and underlying models evolve
• This role goes beyond individual features. You’ll drive technical direction across product areas, aligning product, AI, and infrastructure teams on how to build AI-native systems that scale. You’ll help define patterns for how we evaluate, iterate on, and continuously improve AI-driven experiences, turning ambiguous opportunities into clear systems and execution plans
• You’ll partner closely with product, design, and AI teams to identify high-leverage opportunities, prototype new approaches, and guide them into production—shaping both the product experience and the underlying systems that power it
• Define system architecture for AI-native product surfaces
• Design foundational systems (generation pipelines, data models, evaluation frameworks) that power multiple product areas
• Drive cross-team technical strategy
• Lead initiatives that span product, AI, and infrastructure teams, ensuring alignment on architecture and execution
• Establish best practices for AI product engineering
• Set standards for how we build with AI—covering areas like evaluation, reliability, iteration loops, and system design
• Translate ambiguity into scalable systems and product direction
• Take loosely defined opportunities and turn them into clear technical approaches and execution plans
• Raise the bar across the organization
• Influence engineering quality, system design, and product thinking beyond your immediate team
• Shape how AI accelerates engineering velocity
• Drive adoption and best practices for AI-assisted development, improving how teams design, build, and iterate on product