Careers at Perplexity

In 2026, we launched Computer, the defining product for the new era of agentic AI. We've scaled beyond the millions of people using Perplexity every day for research, shopping, investing and curiosity into a new paradigm of using AI to transform knowledge into action. The Multimodal team builds the experiences and infrastructure that move AI interaction beyond touch and text: realtime voice, vision, and the platform systems behind them. We own the full path from a user speaking into a device to an answer coming back: the realtime session infrastructure that connects clients to frontier audio models, the backend orchestration that routes, records, and supervises live sessions, and the SDK that powers voice and multimodal experiences across Perplexity's apps. As Engineering Manager for Multimodal, you will lead the team building realtime voice and multimodal experiences across Perplexity. You'll hire and develop engineers, set technical direction, and drive new products at the intersection of voice, vision, and agents. Key Responsibilities Lead the team building realtime voice and multimodal experiences across Perplexity, taking new products from first prototype to production launch. Own the team's roadmap, deciding which voice and vision experiences to build next and what infrastructure they need to succeed. Hire and develop engineers, giving them ownership of meaningful technical problems and the feedback to grow. Shape the architecture behind the full voice experience, from a user speaking into a device to models, tools, and agents responding. Lead the systems that turn live conversations into action, connecting voice models to tools, agents, and long-running tasks. Guide the team through the latency, reliability, and scaling challenges of live voice, including session recovery and performance under load. Partner with SDK, client, infrastructure, and model teams to turn new audio and vision capabilities into experiences people can use across our apps. Use user feedback and production performance to improve the experience after launch and decide where the team should invest next. Qualifications Experience managing engineering teams, including hiring, coaching, and performance management. A strong software engineering background in backend or distributed systems. Experience designing and operating production services in rapidly scaling environments on AWS or similar cloud infrastructure. A track record of leading teams to ship complex projects in a fast-moving environment. Strong product judgment and the ability to translate user problems into clear technical priorities. Clear communication and the ability to work effectively across teams. Experience with Rust, Python, Go, or similar languages. We work primarily in Rust and Python. Genuine interest and adoption of AI products and willingness to learn quickly. Nice to have Experience with realtime media systems: voice, audio streaming, WebRTC, or low-latency transport. Experience integrating LLMs, speech models, or computer vision into production systems. Experience with agent frameworks, tool-calling architectures, or sandboxed execution environments. Experience leading projects across backend services, client SDKs, and user-facing applications. Time spent leading a team at a fast-growing startup or in a high-ownership environment.

In 2026, we launched Computer, the defining product for the new era of agentic AI. We've scaled beyond the millions of people using Perplexity every day for research, shopping, investing and curiosity into a new paradigm of using AI to transform knowledge into action. The Multimodal team builds the experiences and infrastructure that move AI interaction beyond touch and text: realtime voice, vision, and the platform systems behind them. We own the full path from a user speaking into a device to an answer coming back: the realtime session infrastructure that connects clients to frontier audio models, the backend orchestration that routes, records, and supervises live sessions, and the SDK that powers voice and multimodal experiences across Perplexity's apps. As Engineering Manager for Multimodal, you will lead the team building realtime voice and multimodal experiences across Perplexity. You'll hire and develop engineers, set technical direction, and drive new products at the intersection of voice, vision, and agents. Key Responsibilities Lead the team building realtime voice and multimodal experiences across Perplexity, taking new products from first prototype to production launch. Own the team's roadmap, deciding which voice and vision experiences to build next and what infrastructure they need to succeed. Hire and develop engineers, giving them ownership of meaningful technical problems and the feedback to grow. Shape the architecture behind the full voice experience, from a user speaking into a device to models, tools, and agents responding. Lead the systems that turn live conversations into action, connecting voice models to tools, agents, and long-running tasks. Guide the team through the latency, reliability, and scaling challenges of live voice, including session recovery and performance under load. Partner with SDK, client, infrastructure, and model teams to turn new audio and vision capabilities into experiences people can use across our apps. Use user feedback and production performance to improve the experience after launch and decide where the team should invest next. Qualifications Experience managing engineering teams, including hiring, coaching, and performance management. A strong software engineering background in backend or distributed systems. Experience designing and operating production services in rapidly scaling environments on AWS or similar cloud infrastructure. A track record of leading teams to ship complex projects in a fast-moving environment. Strong product judgment and the ability to translate user problems into clear technical priorities. Clear communication and the ability to work effectively across teams. Experience with Rust, Python, Go, or similar languages. We work primarily in Rust and Python. Genuine interest and adoption of AI products and willingness to learn quickly. Nice to have Experience with realtime media systems: voice, audio streaming, WebRTC, or low-latency transport. Experience integrating LLMs, speech models, or computer vision into production systems. Experience with agent frameworks, tool-calling architectures, or sandboxed execution environments. Experience leading projects across backend services, client SDKs, and user-facing applications. Time spent leading a team at a fast-growing startup or in a high-ownership environment.

Perplexity is seeking a DevOps engineer to join our small team in revolutionizing the way people search and interact with the internet. You will be responsible for leading the design, implementation, and scaling of the infrastructure, tooling and systems that support our Search feature. The ideal candidate should have experience in designing highly scalable infrastructure, building systems, tools and performing testing, monitoring, and maintenance. Our backend stack includes Python, Go, Rust, PostgreSQL, DynamoDB, Redis, and Kubernetes - built alongside dedicated in-house AI and search interfaces. Responsibilities: Design and implement highly available, high-performance, and scalable systems. Design and implement various tools for other engineers helping them with their day to day job. Design and implement CI/CD and other workflows to enhance stability, robustness and speed of iteration. Maintain and optimize key-value and relational databases. Scale and load balance web server backends to meet rapidly changing needs. Monitor systems and applications, proactively identifying and resolving reliability, scalability, or performance issues. Develop monitoring tools, alerts, and dashboards to provide visibility into system health and performance. Qualifications: Strong experience with cloud infrastructure built on AWS. Proficient in database management and caching strategies. Excellent problem-solving and troubleshooting skills, with the ability to analyze, debug, and resolve complex technical issues. Experience working with containers (Docker, Kubernetes) and orchestration tools. Excellent communication and collaboration skills. Experience with Python and Terraform. 3+ years of DevOps/SRE/System Administration experience.

Perplexity is seeking a DevOps engineer to join our small team in revolutionizing the way people search and interact with the internet. You will be responsible for leading the design, implementation, and scaling of the infrastructure, tooling and systems that support our Search feature. The ideal candidate should have experience in designing highly scalable infrastructure, building systems, tools and performing testing, monitoring, and maintenance. Our backend stack includes Python, Go, Rust, PostgreSQL, DynamoDB, Redis, and Kubernetes - built alongside dedicated in-house AI and search interfaces. Responsibilities: Design and implement highly available, high-performance, and scalable systems. Design and implement various tools for other engineers helping them with their day to day job. Design and implement CI/CD and other workflows to enhance stability, robustness and speed of iteration. Maintain and optimize key-value and relational databases. Scale and load balance web server backends to meet rapidly changing needs. Monitor systems and applications, proactively identifying and resolving reliability, scalability, or performance issues. Develop monitoring tools, alerts, and dashboards to provide visibility into system health and performance. Qualifications: Strong experience with cloud infrastructure built on AWS. Proficient in database management and caching strategies. Excellent problem-solving and troubleshooting skills, with the ability to analyze, debug, and resolve complex technical issues. Experience working with containers (Docker, Kubernetes) and orchestration tools. Excellent communication and collaboration skills. Experience with Python and Terraform. 3+ years of DevOps/SRE/System Administration experience.

Perplexity is seeking a DevOps engineer to join our small team in revolutionizing the way people search and interact with the internet. You will be responsible for leading the design, implementation, and scaling of the infrastructure, tooling and systems that support our Search feature. The ideal candidate should have experience in designing highly scalable infrastructure, building systems, tools and performing testing, monitoring, and maintenance. Our backend stack includes Python, Go, Rust, PostgreSQL, DynamoDB, Redis, and Kubernetes - built alongside dedicated in-house AI and search interfaces. Responsibilities: Design and implement highly available, high-performance, and scalable systems. Design and implement various tools for other engineers helping them with their day to day job. Design and implement CI/CD and other workflows to enhance stability, robustness and speed of iteration. Maintain and optimize key-value and relational databases. Scale and load balance web server backends to meet rapidly changing needs. Monitor systems and applications, proactively identifying and resolving reliability, scalability, or performance issues. Develop monitoring tools, alerts, and dashboards to provide visibility into system health and performance. Qualifications: Strong experience with cloud infrastructure built on AWS. Proficient in database management and caching strategies. Excellent problem-solving and troubleshooting skills, with the ability to analyze, debug, and resolve complex technical issues. Experience working with containers (Docker, Kubernetes) and orchestration tools. Excellent communication and collaboration skills. Experience with Python and Terraform. 3+ years of DevOps/SRE/System Administration experience.

Perplexity is seeking an experienced Machine Learning Research Engineer to help build the next generation of advanced search technologies, with a focus on retrieval and ranking. Responsibilities Relentlessly push search quality forward — through models, data, tools, or any other leverage available Architect and build core components of the search platform and model stack Design, train, and optimize large-scale deep learning models using frameworks like PyTorch, leveraging distributed training (e.g., PyTorch Distributed, DeepSpeed, FSDP) and hardware acceleration, with a focus on retrieval and ranking models Conduct advanced research in representation learning, including contrastive learning, multilingual, and multimodal modeling for search and retrieval Deploy models — from boosting algorithms to LLMs — in a scalable and performant way Build and optimize RAG pipelines for grounding and answer generation Collaborate with Data, AI, Infrastructure, and Product teams to ensure fast and high-quality delivery Qualifications Deep understanding of search and retrieval systems, including quality evaluation principles and metrics Proven track record with large-scale search or recommender systems Strong proficiency with PyTorch, including experience in distributed training techniques and performance optimization for large models Expertise in representation learning, including contrastive learning and embedding space alignment for multilingual and multimodal applications Strong publication record in AI/ML conferences or workshops (e.g., NeurIPS, ICML, ICLR, ACL, CVPR, SIGIR) Self-driven, with a strong sense of ownership and execution Minimum of 3 years (preferably 5+) working on search, recommender systems, or closely related research areas

Perplexity API Platform Perplexity innovates at the frontier of AI infrastructure, search, and orchestration to serve the world's most discerning users. The Perplexity API Platform brings our technology to the world's most discerning developers. From exabyte-scale knowledge indexes to codegen-first agent runtimes, the building blocks behind Perplexity's applications are some of the most battle-tested AI systems in the industry. We believe these same building blocks can and should power the aspirations of builders everywhere. It's one thing to solve planet-scale retrieval, long-horizon orchestration, and other foundational AI challenges within a single product ecosystem. The true measure of success is to turn those solutions into elegant APIs that delight developers and agents alike. Our API Platform delivers frontier intelligence to thousands of customers: startups, trillion-dollar enterprises, U.S. and allied governments, and everyone in between. We've achieved incredible scale, yet we're just getting started. Join us to build tools for curious minds. About this role Perplexity is seeking a strong technical leader to steer the API Platform engineering team through a rapid period of growth. Our company builds technology that reshapes how people search, reason, and interact with the world around them. Week after week, we observe increasing demand for programmatic interfaces to that technology. The API Platform engineering team is charged with designing, implementing, and scaling these interfaces. You and your team will work on an eclectic portfolio spanning distributed systems, performance optimization, agent orchestration, and frontier topics that often change with each passing month. Throughout this work, you'll prioritize great developer and agent experience alike. You'll also define technical strategy for how we scale to meet compounding growth exponentials (number of customers, agents per customer, compute/retrieval per agent, etc.). This role is ideal for seasoned engineering managers who are unusually passionate about providing the world with programmatic access to the building blocks of frontier intelligence. Key Responsibilities Provide both technical and team leadership across multiple layers of our rapidly growing API business. Design, build, and operate mission-critical APIs that provide our customers the building blocks for frontier intelligence. Continually reimagine the customer needs of tomorrow (and the architectures to serve those needs), while faithfully serving the customer workloads of today. Drive product reliability, code quality, AI evaluation, testing, and maintenance for the broader team. Oversee hiring, onboarding, and mentorship for a rapidly growing team; develop rigorous interview pipelines and work closely with recruiting to source candidates. Collaborate across teams to incorporate novel frontier capabilities into the API Platform and improve existing capabilities for API customer needs. Track and ensure progress toward top-line business goals, in close coordination with engineering and business executives. Qualifications Entrepreneurial attitude; able and eager to run more than just engineering. Proficiency in Python (bonus points for Go and/or Rust). Strong understanding of high-traffic API design: schema evolution & versioning, idempotency, authentication patterns, rate limiting, and performance tuning. Experience with modern AI APIs (including latency tuning, streaming, model orchestration, emerging technical standards) is a strong plus. Strong customer empathy and product sense, ensuring the APIs you build are ergonomic, well-documented, and easy to adopt for developers and agents alike. Strong organizational skills for managing and delivering parallel technical projects; ability to guide highly-opinionated teams in making sound tradeoffs and prioritization decisions is critical. Experience managing engineering teams, including recruiting, growing, and retaining high-caliber talent. 8+ years of engineering experience, with at least 3 of those years as an engineering manager.

Perplexity is seeking a TLM (Tech Lead Manager) to lead and grow our highly driven Agents engineering team. The Agents team consists of AI/ML, backend, and full-stack engineers who collaborate to build delightful agentic experiences within our Comet ecosystem . Our vision is to empower our users with AI agents that can faithfully actualize their intent, however and wherever expressed, through open-ended interactions with the world. As the Agents TLM, you will bring AI expertise, sharp product intuition, and strong engineering management skills to advance the frontier of what agents can accomplish for our millions of devoted users. You will lead, grow, and support a team in solving many open problems in AI, including: Designing AI agents to navigate the digital world and perform increasingly valuable units of work for our users; Training action and decision models that determine, based on complex multimodal states, how to accomplish user-specified objectives; Providing consistently excellent experiences across desktop, mobile, headless cloud, and other environments through flexible abstractions and frictionless backgrounding; Developing permission architectures, payload classifiers, and other methods to implement secure-by-design agentic capabilities; Designing optimal data representations and modes of interaction between agents and their environments; and much, much more. Responsibilities Provide technical leadership across multiple layers of a rapidly growing product in the AI agents space. Develop and leverage cutting-edge AI models, infrastructure, and browser technologies to advance the capability frontier and scale those capabilities for a rapidly growing userbase. Exercise sharp technical & product intuition to guide the team’s system architectures and product roadmaps. Drive product reliability, code quality, AI evaluation, testing, and maintenance for the broader team. Oversee hiring, onboarding, and mentorship for a rapidly growing team. Develop rigorous interview pipelines and work closely with recruiting to source candidates. Interface with the Perplexity co-founders to deliver strategic objectives that redefine what’s possible in the AI industry. Qualifications Strong foundational familiarity with the full AI product stack. Proficiency in Python (bonus points for TypeScript, Go, and/or Rust). Domain expertise in at least one of the following areas: Context engineering and tool interfaces for frontier AI models Post-training and reinforcement learning (particularly for multimodal models) Browser technologies (CDP, Playwright, extension development, etc.) Strong product intuition and taste for user experience excellence. Strong background and hands-on technical experience with frontier models (the more relevant to open-world agents, the better). Strong organizational skills for managing and delivering parallel technical projects; ability to guide highly-opinionated teams in making sound tradeoffs and prioritization decisions is critical. Experience managing engineering teams, including recruiting, growing, and retaining high-caliber talent. 8+ years of engineering experience, with at least 3 of those years as an engineering manager.

Perplexity is seeking energetic engineers to join our highly driven Agents engineering team. The Agents team consists of backend, full-stack, and AI/ML engineers who collaborate to build harnesses and AI systems powering delightful agentic experiences. These experiences include Perplexity Computer (our platform for generalized frontier intelligence), the Comet ecosystem , our Agent API, and more. Our vision is to empower our users with agents that can faithfully actualize their intent, however and wherever expressed, through open-ended interactions with the world. As an engineer on our Agents team, you will bring AI expertise, sharp product intuition, and a tinkerer's mindset to advance the frontier of what agents can accomplish for our millions of devoted users. You will work across applied research and engineering to solve many open problems in AI, including: Designing AI agents to navigate the digital world and perform increasingly valuable units of work for our users; Training action and decision models that determine, based on complex multimodal states, how to accomplish user-specified objectives; Providing consistently excellent experiences across desktop, mobile, headless cloud, and other environments through flexible abstractions and frictionless backgrounding; Developing permission architectures, payload classifiers, and other methods to implement secure-by-design agentic capabilities; Designing optimal data representations and modes of interaction between agents and their environments; and much, much more. Responsibilities Engineer agent harnesses that connect powerful models with the environments and tools required to perform economically valuable work for users. Drive cutting-edge AI capabilities across multiple layers of a rapidly growing product in the AI agents space. Develop and leverage cutting-edge AI models, infrastructure, and browser technologies to advance the capability frontier and scale those capabilities for a rapidly growing userbase. Ensure a high craft and quality bar, in both AI agent performance and user experience. Collaborate with fellow engineers, designers, product managers, data scientists, and others across the company to integrate core Perplexity functionality into our frontier agentic products and vice-versa. Contribute to product reliability, code quality, AI evaluation, testing, and maintenance across the broader team. Qualifications Strong foundational familiarity with the full AI product stack. Proficiency in Python (bonus points for TypeScript, Go, and/or Rust). Significant experience in at least one of the following areas: Context engineering and tool interfaces for frontier AI models Post-training and reinforcement learning (particularly for multimodal models) Browser technologies (CDP, Playwright, extension development, etc.) Strong product intuition and taste for user experience excellence. Comfortable working with a small, fast-moving team, must be willing to dive in and take ownership. A passion for shipping products that surprise and delight.

Perplexity Computer is one of the defining products of the new era of agentic AI. Millions of people use Perplexity to transform knowledge into action, and the Agent Capabilities team sits at the intersection of frontier AI research and product innovation, building the foundations that shape how users and agents solve increasingly complex tasks. As every major breakthrough in AI models creates new possibilities, the Agent Capabilities team is responsible for turning frontier AI breakthroughs into reusable product capabilities. We are often the first to evaluate emerging model capabilities, determine where they create real user value, and transform them into reliable, scalable, high quality experiences for both users and agents. This is a highly leveraged role with broad ownership at the intersection of frontier AI research, agent systems, platform engineering, and product innovation. Tech Stack : Python | Go | Rust | PostgreSQL | DynamoDB | AWS | TypeScript Why Perplexity is different Craftsmanship . We build high quality, tasteful products targeting both the AI native and AI curious. Ownership . You identify the problem, design the solution and ship it. Entrepreneurship . We think like founders, act with urgency, and hustle to deliver for each other and our users. Scholarship . Work among highly talented peers, pursuing knowledge and truth, upleveling ourselves, our teams, and our products. Partnership . We amplify each others' strengths, break down silos, and give selflessly to help our colleagues deliver excellence. What you'll do Evaluate frontier models against real user tasks, identify useful behaviors and failure modes, and turn the most promising advances into production agent systems. Own the lifecycle from rapid prototyping and evaluation through launch, monitoring, and iteration. Improve agents’ ability to plan, use tools, manage context, recover from errors, and complete long-running tasks reliably. Apply state of the art ML and LLM techniques to design scalable agent capabilities such as skills, plugins, artifact generation, tools integrate and use, auto-research, and multi-agent collaboration. Shape the architecture, abstractions, and product experiences that enable both users and agents to compose increasingly sophisticated solutions for real-world tasks. Own agent behavior and capabilities end-to-end, from user-facing products and interfaces to backend services. Define offline and online evaluations for task completion, correctness, safety, latency, cost, and user satisfaction. Iteratively improve across models, prompts, harnesses, and products for different problem spaces. Build secure, observable, and reliable agent systems, including permissions and safeguards for sensitive actions. Develop tracing, replay, and monitoring infrastructure that makes agent failures reproducible and actionable. Collaborate closely with PM, Data Science, Research, to identify high-impact opportunities in understanding and validating emerging model capabilities, and turn complex agent behaviors into simple, reliable product experiences. Apply relevant advances in models, inference, evaluation, and agent architecture when they produce measurable improvements in production performance. Set technical direction on ambiguous problems and raise the bar through design reviews, mentorship, and technical leadership. Qualifications Typically 6+ years of professional software engineering experience, with a track record of building and owning robust AI-powered, large-scale, user-facing or data-intensive products. Exceptional candidates with less experience and an outstanding record of impact are encouraged to apply. Strong software engineering fundamentals, with experience building and operating AI/ML products, backend services, or distributed systems at scale. Experience owning the AI product lifecycle, including data analysis, rigorous evaluation, production monitoring, and iterative improvement. Able to define metrics and use production data and user feedback to guide decisions. Practical experience in one or more relevant areas, such as agent harnesses, tool use, context engineering, model evaluation, browser automation, or long-running task execution. Strong product judgment and execution: you can translate ambiguous user needs into applied AI or ML problems and ship durable solutions with measurable user impact. Genuine interest in frontier AI capabilities, agent systems, and excitement for rapidly exploring, evaluating, and productizing new model behaviors. Nice to have Experience with LLM context engineering or harness engineering, experience with subagents, coding assistants, long-running or autonomous task execution. Deep familiarity with the strengths and limitations of current model families across reasoning, tool use, context management, and long-horizon tasks. Experience building agent permissions, safeguards, evaluation infrastructure, or production observability systems. Experience with mid-training, post-training, or reinforcement learning for frontier or open-source models, along with a strong understanding of model strengths and limitations across reasoning, tool use, context management, and long-horizon tasks. AI/ML research experience demonstrated through publications, open-source contributions, or other meaningful research impact. Time spent at a fast-growing startup or on a high-ownership engineering team.