Senior Software Engineer, Otter.ai

• Has 5+ years of experience building and scaling product-facing systems, with a track record of owning complex features or product areas end-to-end
• Writes clean, maintainable code (Python preferred) and makes strong architecture and design decisions across a modern web stack
• Brings a high bar for product quality, not just system correctness — consistently asks whether what's being built actually serves users well
• Has experience working with AI/LLM-powered systems, or can ramp quickly and contribute meaningfully to shaping their behavior in production
• Drives projects from idea → production with strong ownership, and helps others do the same through mentorship and technical leadership
• Thrives in ambiguous, fast-moving environments and can set technical direction, not just execute within it
• Exposure to user feedback loops, experimentation, or evaluation frameworks

Desirable

• As a Senior Software Engineer on our Product teams, you’ll own significant areas of the product and play a key role in shaping how AI capabilities translate into real user value
• You’ll work across the full lifecycle of AI-driven features—from data ingestion and model orchestration to output structuring and delivery into user-facing product surfaces. In this role, you’ll not only build features, but also design the systems that power them—ensuring that AI outputs are reliable, performant, and aligned with real user needs
• You’ll take on complex, ambiguous problems and drive them from concept to production, making thoughtful tradeoffs across latency, cost, and quality. This includes defining how LLMs, retrieval systems, and structured data come together to create cohesive product experiences
• Working closely with product, design, and AI teams, you’ll rapidly prototype and iterate on features like summaries, action items, and intelligent workflows—while helping establish patterns and best practices that other engineers can build on
• You’ll also play a key role in elevating the team: guiding technical decisions, mentoring engineers, and raising the bar for both product thinking and engineering quality
• Own end-to-end delivery of AI product features
• Lead the design and implementation of complex features—from initial concept through production—ensuring high quality and strong user impact
• Drive system design for AI-backed experiences
• Architect systems that orchestrate LLMs, retrieval, and structured data, making thoughtful tradeoffs between flexibility, reliability, and performance
• Elevate product quality through iteration and evaluation
• Establish and improve feedback loops (evaluation frameworks, user signals, experimentation) to systematically improve AI output quality
• Lead technical direction within a product area
• Break down ambiguous problems, define approaches, and guide execution across multiple engineers
• Mentor and raise the engineering bar
• Provide guidance on code quality, system design, and product thinking; help less experienced engineers operate more effectively in an AI-driven environment
• Accelerate team velocity through AI-assisted development
• Model effective use of modern AI tools to improve iteration speed, code quality, and overall team productivity