Software Engineer, Product

Pika Labs Pika Labs · AI Frontier · Palo Alto, CA · Engineering

Staff Software Engineer, Product role at Pika Labs focused on shaping and scaling user-facing systems for their AI-powered platform. The role involves leading the architecture and delivery of product features, including user interfaces, collaboration tools, real-time interactions, and generative AI-powered workflows. Emphasis on end-to-end project ownership, technical excellence, and mentorship.

What you'd actually do

  1. Lead User-Facing Product Engineering: Architect and develop intuitive, performant, and scalable user-facing features and applications for Pika’s web and multi-platform products.
  2. Shape Product Experiences: Collaborate closely with product and design teams to deliver features that delight users and solve real problems, ensuring a seamless and accessible creative workflow.
  3. Drive End-to-End Projects: Take ownership of product features from ideation and specification through development, launch, and ongoing improvement.
  4. Architect Real-Time Collaboration: Build and scale systems that support real-time multi-user interactions, messaging, and live collaboration.
  5. Integrate Advanced AI Workflows: Design and optimize product features that harness generative AI (LLMs, models, and agentic workflows) to power creative tools.
  6. Champion Technical Excellence: Write and review technical proposals, evaluate technical and product trade-offs, and mentor other engineers to drive best practices and align on great product outcomes.

Skills

Required

  • 5+ years of software engineering experience
  • 2+ years in senior, product-focused roles building web or mobile products at scale
  • Deep proficiency in modern frontend and/or backend technologies (React, TypeScript, Node.js, Go, or similar)
  • Scalable architecture patterns
  • Strong understanding of distributed systems
  • Cloud infrastructure (AWS/GCP)
  • Building reliable, high-traffic services
  • Strong written and verbal communication

Nice to have

  • Experience with real-time collaboration
  • Creative tools
  • Media-rich applications
  • Familiarity with generative AI and agentic product patterns
  • Experience at fast-growing startups
  • Experience in ambiguous, high-velocity environments
  • Competitive coding, hackathon, or open-source experience

What the JD emphasized

  • generative AI (LLMs, models, and agentic workflows)

Other signals

  • user-facing systems
  • generative AI-powered workflows
  • millions of users
  • architectural decisions
  • technical mentorship