Perplexity

Perplexity is looking for a highly skilled Expert Systems Engineer to join our Search Core team. For the indexing and data processing stream. This role is critical to building next-generation search products and technologies. You will help drive key decisions around the architecture, design, and implementation of foundational components in our technical stack. Responsibilities - Design and build core search engine components, especially indexing pipelines, data storage formats that operate at the scale of billions of pages - Develop streaming and batch data processing with YT systems for search index construction in a high-load environment - Push the limits of hardware performance through low-level optimizations and systems-level tuning - Tackle challenges in multithreading, concurrency, and system-level optimization - Design and build core search engine components, including indexing pipelines, retrieval algorithms, and ranking systems that operate at the scale of billions of pages - Develop streaming and batch data processing systems for search index construction in a high-load environment - Push the limits of hardware performance through low-level optimizations and systems-level tuning - Tackle challenges in multithreading, concurrency, and system-level optimization Qualifications - 3+ years of hands-on experience in systems programming (Rust, C++, C, or similar) - Ownership of full project lifecycle — you don't just write a fast inner loop, you care about how the system is built, deployed, operated, and scaled in production - Knowledge of Python or other scripting languages - Knowledge of Data processing systems (YT/Kafka/Hadoop) - Passion for writing clean, efficient, and scalable systems-level code - Strong knowledge of algorithms and data structures, and the ability to apply them effectively - Deep understanding of multithreading, including various approaches, challenges, and trade-offs - Experience building high-load, distributed, and hardware-adjacent services - Solid understanding of Linux internals (syscalls, networking stack, memory model, kernel tuning) - Familiarity with low-level optimization techniques (memory management, cache efficiency, SIMD, profiling) Preferred Qualifications - Experience developing core components of search engines, databases, or information retrieval systems - Understanding of search fundamentals: indexing, query parsing, ranking, and relevance - Experience with trading systems or other latency-sensitive real-time systems - Familiarity with cloud services, Kubernetes, and AWS infrastructure

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 https://www.perplexity.ai/comet. 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 https://www.perplexity.ai/computer (our platform for generalized frontier intelligence), the Comet ecosystem https://www.perplexity.ai/comet, 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.

ABOUT THE ROLE The Infrastructure team builds and operates the foundational systems behind Perplexity’s products. At Perplexity, infrastructure sits on the critical path of every answer, supporting real-time search, retrieval, model serving, and agent workloads where latency, reliability, and rapid iteration directly shape the user experience. This role is for strong infrastructure engineers whose experience spans multiple domains and who are energized by cross-cutting problems that do not fit neatly within a single platform team. You do not need to be a specialist in every area. Scope ranges from owning major production systems to setting technical direction across teams, leading complex infrastructure programs, and shaping infrastructure strategy across the organization. If a specialized Cloud Infrastructure, Storage Platform, Backend Platform, Data Platform, Connector Platform, or AI Acceleration role clearly matches your expertise and interests, apply directly to it. If your experience spans several infrastructure domains or you are most energized by cross-cutting systems problems, apply here. Submit one application, and we will consider you across the Infrastructure organization. KEY RESPONSIBILITIES - Own cross-cutting infrastructure problems that span compute, storage, networking, data, deployment, and reliability, including eliminating bottlenecks across retrieval and serving paths, building shared abstractions across deployment environments, and resolving failure modes that cross platform boundaries. - Design, build, and operate distributed infrastructure supporting Perplexity’s consumer, AI, and enterprise workloads, owning systems from architecture through production operation. - Identify gaps between existing platforms and build shared abstractions, automation, and tooling that make infrastructure easier and safer to use. - Improve system performance, availability, scalability, and cost-efficiency across online request traffic and background workloads. - Debug complex production issues across service and infrastructure boundaries, then turn the findings into durable architectural improvements. - Set technical direction for complex infrastructure systems, lead high-impact programs across teams, and establish durable technical standards through collaboration with infrastructure, product, AI, and security partners. QUALIFICATIONS - 4+ years of professional software engineering experience building and operating production backend, platform, or distributed systems. - A track record of owning complex production systems end to end and delivering sustained technical impact across teams. - Demonstrated ability to set technical direction, lead through influence, and raise the engineering bar through architecture, design reviews, and mentorship. - Strong software engineering skills in Python or other systems or backend languages such as Go, Rust, C++, or Java. - Meaningful experience across at least two infrastructure domains, such as cloud platforms, distributed systems, Kubernetes, storage, databases, networking, data systems, developer infrastructure, or production reliability. - Ability to develop depth quickly in unfamiliar systems, reason across software and infrastructure layers, and drive production incidents from diagnosis through durable resolution. If you’re excited about this role, we encourage you to apply even if your experience doesn’t match every qualification listed above.