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Member of Technical Staff (Software Engineer, Enterprise Adoption)

Join Perplexity's Enterprise Adoption team to enhance AI tools for internal and external users in a transformative role.

Location
San Francisco
Compensation
Not disclosed
Level
mid
Type
full time

Skills & Technologies

AI in the day-to-day

Perplexity uses AI tools across everything we do, from frontend and backend engineering to applied AI research and business operations.

Requirements

Experience
4+ years

Joblaze summary

In this role, the engineer focuses on enhancing the use of Perplexity's AI tools across various internal teams, ensuring these systems effectively support enterprise operations. Key skills include proficiency in Python and familiarity with AI models, as well as an understanding of the needs of non-technical staff. This position is ideal for experienced software engineers who are curious about business processes and eager to bridge the gap between technology and user experience. The Enterprise Adoption team is pivotal in driving the company's mission to transform organizational interactions with AI.

Joblaze insights

Quick facts

How much experience is required?
At least 4 years of relevant experience for this Member of Technical Staff (Software Engineer, Enterprise Adoption) role.
What's the tech stack?
Joblaze extracted these technologies from the posting: TypeScript, AI/ML, Go, Python.
What seniority level is this role?
Perplexity targets mid-level candidates for this position.
Is this full-time or contract?
Full-time for this Member of Technical Staff (Software Engineer, Enterprise Adoption) role at Perplexity.

From the original posting

Perplexity is seeking creative, AI native engineers to join our Enterprise Adoption team. Our company is reshaping the way people interact with AI agents within organizations. The Enterprise Adoption team's mandate is to continually uplevel the way our company and our customers use Perplexity Computer as the instrument of that transformation to deliver new ways of working in the agentic future.

Just as Perplexity is heralding an agentic future for the internet, you will ensure that the company makes our AI tools and agents a perfect fit for our growing Enterprise business. Today, Perplexity uses AI tools across everything we do, from frontend and backend engineering to applied AI research and business operations. Some of your users will be our own teams, from recruiting and go-to-market to finance, legal, support, and operations, and you will engineer the core systems that make Computer an indispensable multiplier of their craft. Learnings from our internal teams will also be applied for our enterprise customers, bringing frontier AI working patterns to external organizations.

What you’ll do

  • 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.

  • 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.

  • 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.

  • 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.

  • Collaborate closely with PM, Design, Data Science, Sales, and Enterprise customers to turn any process need into simple, reliable product experiences in Computer.

Qualifications

  • 4+ years of professional software engineering experience. Familiarity with building platforms for enterprise or internal users is a plus.

  • Daily use of AI models/tools, with strong knowledge on the latest frontier.

  • Proficiency with Python, along with experience and/or TypeScript, Go, and other languages.

  • Strong understanding of the work of non-technical staff across enterprises, along with a curiosity about the work of business and operations teams, who will be your users.

  • Broad working knowledge of the modern AI agent stack (agents, connectors, context engineering, and evals), along with strong intuition for where today's agents shine and where they fall down. (For example: you don't need to have authored an MCP server, but you should know what MCP is and when/where/why it's used.)

  • Strong product judgement, you can make decisions that will simplify the agent user experience for customers with a range of technical abilities.