Software Engineer, Enterprise Adoption at Perplexity, New York

Neolife Updates; New York (NY); On-site; USD 220,000 - 405,000; Full time

Job summary

Perplexity is seeking creative, AI-native engineers to join its Enterprise Adoption team in New York, NY. As a Member of Technical Staff (Software Engineer, Enterprise Adoption), you will engineer core systems that multiply the impact of Perplexity for enterprise customers.

Your users will include internal teams—recruiting, go-to-market, finance, legal, support, and operations—as well as external enterprise customers.

Qualifications

• 4+ years of professional software engineering experience.
• Experience building platforms for internal users is a plus.
• Strong knowledge of AI models and frontier developments.
• Proficiency in Python; experience with TypeScript or Go.

Responsibilities

• Identify and execute high-potential opportunities to make Perplexity transformative for every team.
• Develop empathy for the workflows of technical and business teams.
• Engineer connectors, skills, and evaluation infrastructure for scalable use cases.
• Close the loop between internal usage and product improvements.
• Collaborate cross-functionally with PM, Design, Data Science, Sales, and enterprise customers.

Skills

4+ years software engineering

AI fluency

Python

TypeScript

Go

Context engineering

Agent frameworks

Product judgement

Tools

LangChain

LlamaIndex

MCP

Job description

Perplexity is seeking creative, AI-native engineers to join its Enterprise Adoption team in New York, NY. As a Member of Technical Staff (Software Engineer, Enterprise Adoption), you will engineer the core systems that make Perplexity Computer an indispensable multiplier for teams across the company and its enterprise customers.

Member of Technical Staff (Software Engineer, Enterprise Adoption) at Perplexity

The Enterprise Adoption team's mandate is to continually uplevel how Perplexity and its customers use Computer as the instrument of transformation—delivering new ways of working in an agentic future. Today, AI tools are embedded across everything Perplexity does, from frontend and backend engineering to applied AI research and business operations.

Your users will include internal teams—recruiting, go-to-market, finance, legal, support, and operations—as well as external enterprise customers. Learnings from internal usage will be applied directly to the product, bringing frontier AI working patterns to external organizations.

What You Will Do

• Identify and execute on the highest-potential opportunities to make Computer transformative for every team, building core systems that bring those opportunities within reach.
• Develop empathy for the nuances of technical and business teams' work across disciplines, collaborating to harness AI in new ways.
• Engineer connectors, skills, and evaluation infrastructure that make knowledge stores and human-orchestrated processes legible to Computer, unlocking use cases at scale.
• Close the loop between internal usage and the product itself, translating real-world friction into core platform improvements.
• Collaborate cross-functionally with PM, Design, Data Science, Sales, and enterprise customers to turn process needs into reliable product experiences.

Key Qualifications

• Experience: 4+ years of professional software engineering; familiarity with building platforms for enterprise or internal users is a plus.
• AI fluency: Daily use of AI models and tools, with strong knowledge of the latest frontier developments.
• Technical skills: Proficiency in Python, plus experience with TypeScript, Go, or other languages.
• Domain understanding: Strong grasp of non-technical staff workflows across enterprises, with curiosity about business and operations functions.
• AI agent stack knowledge: Broad working knowledge of agents, connectors, context engineering, and evals—knowing where today's agents excel and where they fall short. (For example: you don't need to have authored an MCP server, but you should know what MCP is and when, where, and why it's used.)
• Product judgement: Ability to simplify the agent user experience for customers with varying technical abilities.

Compensation: USD 220,000 – 405,000 per year (verified). This is a full-time position with an application deadline of 2026-11-19.

Application Tips for Engineering Candidates

• Showcase AI agent work: If you have built tools using LangChain, LlamaIndex, or MCP-compatible servers, highlight these projects prominently. Even personal experiments with agent evals or context engineering demonstrate relevant frontier knowledge.
• Demonstrate cross-functional empathy: Include examples where you shipped internal tools or platforms adopted by non-technical teams—sales, ops, finance. Quantify adoption metrics where possible.
• Highlight Python and systems work: Since the role involves building connectors and evaluation infrastructure, emphasize backend systems design, API integration, and data pipeline experience over purely frontend contributions.
• Study the agentic ecosystem: Familiarize yourself with Model Context Protocol (MCP), agent evaluation frameworks, and current limitations of tool-using LLMs. Being able to discuss trade-offs in agent architectures will set you apart.

If you are passionate about engineering the systems that make AI agents indispensable in real workplaces, this role offers a chance to operate at the frontier of enterprise AI adoption.