Perplexity AI posts all of its official job openings on its own careers pages and uses those listings as the authoritative source of truth for anyone interested in working at the company. If you want to work at Perplexity, the correct starting point is always the careers hub at perplexity.ai/hub/careers or, for New York–based roles, perplexity.ai/hub/careers-nyc. These pages outline not only what jobs are open, but also how Perplexity thinks about talent, growth, and the future of AI-driven products.
At a practical level, Perplexity’s careers ecosystem is organized around four broad pillars: engineering, research, product, and operations. Engineering and AI roles dominate the listings, reflecting the company’s core identity as an applied AI and search technology company. Roles such as Software Engineer, AI Inference Engineer, Backend Software Engineer, and AI Research Scientist form the backbone of the organization. Product roles like Product Manager for Agents and Product Quality Assurance Lead translate technical capability into usable experiences. Operations roles in finance, customer success, and people operations support the business as it scales.
The structure of Perplexity’s hiring also reveals its priorities. There are no roles in traditional hardware, civil, mechanical, or electrical engineering. There are no manufacturing, logistics, or physical infrastructure positions. Everything points inward toward software, models, data, trust, and user experience. This is a company building a digital, knowledge-based product, and its careers reflect that focus with unusual clarity.
Understanding Perplexity careers therefore means more than reading job titles. It means understanding how the company is positioning itself in the AI ecosystem, what skills it values, where it is investing geographically, and how candidates can realistically navigate the process of joining.
Read: Perplexity AI Business Fellowship Explained
The Structure of Perplexity’s Careers Pages
Perplexity maintains two main public entry points for hiring. The global careers page lists roles across locations and functions, while the New York City careers page highlights roles tied specifically to the company’s growing NYC presence.
The global page groups jobs into clear categories: Engineering, AI / Machine Learning, Product, Design, Operations, and Business. Each listing includes a role description, core responsibilities, qualifications, and an application link that routes through Perplexity’s applicant tracking system, most often Greenhouse.
The New York City page functions as a filtered lens on that same system. It highlights roles physically based in NYC or strongly connected to the New York team. These roles tend to cluster around security, frontend engineering, product quality, and developer relations, suggesting that Perplexity is using NYC as a hub for product polish, trust, and ecosystem growth rather than only for core model research.
This separation between a global page and a city-specific page is not cosmetic. It reflects how Perplexity is scaling in a controlled, intentional way, building specialized centers of expertise rather than treating location as an afterthought.
Key Open Role Categories
Perplexity’s job listings consistently fall into a small number of repeat categories. The most visible and numerous are engineering and AI roles.
| Category | Example Roles | Focus |
|---|---|---|
| Engineering | Backend Software Engineer, Frontend Engineer | Scalable systems and product delivery |
| AI / ML | AI Inference Engineer, AI Research Scientist | Models, training, deployment |
| Product | Product Manager – Agents, Product QA Lead | Translating tech into user value |
| Operations | Finance Manager, Customer Success | Business and user support |
Engineering roles focus on building and maintaining the systems that power Perplexity’s products, including search, agents, and model serving infrastructure. AI roles focus on improving the intelligence layer itself, from post-training research to inference optimization. Product roles focus on ensuring those systems actually solve user problems, while operations roles ensure the company can function sustainably as it grows.
This structure mirrors a broader pattern in AI companies: a heavy technical core surrounded by smaller but essential layers of product and business expertise.
Engineering at the Core
Engineering roles form the largest and most central category at Perplexity. These roles are not generic software positions. They are tightly tied to large-scale distributed systems, AI model integration, and performance optimization.
Software Engineers at Perplexity are expected to work on high-traffic, latency-sensitive systems. Backend engineers focus on scalable services, data pipelines, and reliability. Frontend engineers focus on building interfaces that make complex AI behavior understandable and usable to everyday users.
AI Inference Engineers represent a particularly important bridge role. They sit between research and production, ensuring that models can be deployed efficiently, safely, and at scale. This reflects a shift in the AI industry: success is no longer only about building models, but about serving them reliably to millions of users.
Research and the Scientific Layer
While engineering dominates numerically, research remains symbolically important. Roles like AI Research Scientist and Post-Training Researcher focus on improving model behavior, safety, and reasoning quality.
These roles tend to require deep technical and academic backgrounds, often in machine learning, statistics, or computer science. However, Perplexity’s listings emphasize applied research rather than purely theoretical work. The expectation is that research directly informs product improvements, not that it lives in isolation.
This applied research model reflects Perplexity’s identity as a product company first and a lab second.
Product, Trust, and Quality
Product roles at Perplexity play a critical connective function. A Product Manager for Agents, for example, is responsible for shaping how AI agents behave, what problems they solve, and how users interact with them.
Quality assurance and security roles, especially prominent on the NYC page, reflect Perplexity’s emphasis on trust. As an AI search engine dealing with information integrity, hallucinations, and user reliance, quality and safety are not optional add-ons. They are core to the product’s legitimacy.
These roles ensure that the company’s rapid innovation does not come at the expense of reliability, ethics, or user trust.
The Application Process
Perplexity routes most applications through Greenhouse, even when candidates discover roles through LinkedIn or the Perplexity website. This creates a centralized system for resume submission, interview tracking, and communication.
The typical application path looks like this:
| Step | Description |
|---|---|
| Discover | Find the role on Perplexity careers, NYC page, LinkedIn, or Greenhouse |
| Apply | Submit resume and materials via Greenhouse |
| Screening | Recruiter or hiring manager review |
| Interviews | Technical, behavioral, and cross-functional rounds |
| Decision | Offer or feedback |
Candidates are expected to tailor their applications to the specific role, emphasizing not just skills but relevance to Perplexity’s mission of improving access to reliable information.
What Perplexity Looks For
Across roles, Perplexity appears to value three things consistently: technical depth, product thinking, and mission alignment.
Expert commentary on AI hiring emphasizes that top candidates combine strong engineering or research skills with the ability to think about user impact and system-level consequences.
“AI roles demand both depth in algorithms and clarity in communicating complex ideas to cross-functional teams.”
“Security engineering in AI companies is about anticipating threats before users ever experience them.”
“High-growth tech companies increasingly reward engineers who think like product builders, not just coders.”
These perspectives match the structure of Perplexity’s roles, which consistently blend technical and strategic responsibilities.
Takeaways
- Perplexity AI’s careers are organized around engineering, AI research, product, and operations.
- Engineering and AI roles dominate, reflecting the company’s product-first, model-driven focus.
- New York City roles emphasize security, frontend, quality, and ecosystem growth.
- There are no roles in traditional hardware or physical engineering disciplines.
- Applications flow primarily through Greenhouse, even when discovered elsewhere.
- Mission alignment and product thinking matter alongside technical skill.
Conclusion
Perplexity AI’s careers ecosystem offers a window into how modern AI companies are built. It is not a sprawling corporate hierarchy, nor a purely academic lab. It is a tightly focused organization built around software, models, and the responsible delivery of intelligence to users.
For candidates, this means opportunity and responsibility come together. Working at Perplexity means contributing not just to a product, but to a shift in how people search for, trust, and use information. The company’s hiring reflects that seriousness. Roles are specialized, expectations are high, and the impact of the work is direct.
As AI becomes more central to everyday life, companies like Perplexity will increasingly shape how knowledge itself is mediated. Their careers pages are therefore not just job boards. They are maps of where the future of digital work is heading.
FAQs
Where are Perplexity AI jobs posted?
On perplexity.ai/hub/careers, perplexity.ai/hub/careers-nyc, Greenhouse, and LinkedIn.
Does Perplexity hire outside engineering?
Yes, in product, operations, finance, and customer success, though engineering and AI dominate.
Are there hardware or mechanical roles?
No, current listings focus exclusively on software, AI, and business functions.
Do I need a PhD for research roles?
Not always, but advanced expertise in AI or machine learning is typically required.
What skills matter most?
Strong programming or research skills, product awareness, and alignment with Perplexity’s mission.
