Member of Technical Staff (software Engineer, Enterprise Adoption)

Perplexity Perplexity · AI Frontier · San Francisco, CA · Platform & Infrastructure

Software Engineer for the Enterprise Adoption team at Perplexity, focusing on integrating AI agents into enterprise workflows. The role involves building core systems to make AI tools indispensable for internal teams and enterprise customers, translating real-world usage into product improvements, and collaborating across functions to create seamless AI product experiences.

What you'd actually do

  1. Identify, prioritize, and execute on the highest-potential opportunities to make Computer transformative for every team at Perplexity, building the core systems that bring those opportunities within reach.
  2. Develop empathy for the nuances of our technical and business teams' work across disciplines and verticals (recruiting, sales, finance, support, legal, and operations), toward collaborating with them to harness AI in new ways.
  3. Make our knowledge stores, systems, and human-orchestrated processes legible to Computer, engineering the connectors, skills, and evaluation infrastructure that unlock each team's use cases at scale.
  4. Close the loop between internal usage and the Computer product itself, translating the friction and triumphs of real work into core product and platform improvements.
  5. Collaborate closely with PM, Design, Data Science, Sales, and Enterprise customers to turn any process need into simple, reliable product experiences in Computer.

Skills

Required

  • 4+ years of professional software engineering experience
  • Proficiency with Python
  • experience and/or TypeScript, Go, and other languages
  • Strong understanding of the work of non-technical staff across enterprises
  • curiosity about the work of business and operations teams
  • Broad working knowledge of the modern AI agent stack (agents, connectors, context engineering, and evals)
  • Strong product judgement

Nice to have

  • Familiarity with building platforms for enterprise or internal users is a plus.

What the JD emphasized

  • AI native engineers
  • agentic future
  • AI tools and agents
  • core systems
  • evaluation infrastructure
  • modern AI agent stack

Other signals

  • AI native engineers
  • reshaping the way people interact with AI agents
  • deliver new ways of working in the agentic future
  • makes our AI tools and agents a perfect fit for our growing Enterprise business
  • internal usage and the Computer product itself
  • translating the friction and triumphs of real work into core product and platform improvements
  • modern AI agent stack