Member of Technical Staff (Software Engineer, Applied AI)

About the Role The Enterprise AI Products team builds products that make AI part of how teams work together, not just a tool people use on their own. We bring Perplexity Computer into Slack, Microsoft Teams, Microsoft Office, and MCP server with helping teams collaborate with agents and automate work across conversations, documents, and business systems. That includes workflows that start from a message or business event, carry out multiple steps, and bring people in for decisions and approvals. You’ll build new products from the ground up, working directly with customers to understand their problems and shape what we build next. You’ll combine applied AI engineering with product judgment, moving quickly from prototypes to reliable products that solve recurring problems across many organizations. Ownership extends beyond launch: you’ll use customer feedback and product experiments to improve the experience, grow adoption, and make Computer something teams depend on in their daily work. Key Responsibilities Design and build AI-powered experiences in Slack, Microsoft Teams, Microsoft Office, and the MCP server bringing Computer into the tools where teams communicate, create, and coordinate work. Build workflow and automation products that let teams delegate recurring, multi-step tasks to agents, including scheduled and event-triggered execution, human approvals, and visibility into progress and results. Build shared agent experiences that let teams delegate work, review results, and build on each other’s workflows, with clear ownership and handoffs between people and agents. Work directly with customers and internal teams to identify high-impact problems, validate ideas through rapid prototyping, and turn successful use cases into scalable, reusable products. Own products end to end, from problem definition and technical design through full-stack implementation, launch, and production reliability. Measure and improve activation, repeat usage, and workflow completion,

In 2026, we launched Computer, the defining product for the new era of agentic AI. Millions of people now use Perplexity to transform knowledge into action, and the Growth team owns the product loops that help them discover, adopt, and build lasting habits around our most important AI experiences. As a growth engineer at Perplexity, you'll work across the full funnel — activation, onboarding, SEO, lifecycle, conversion, retention, and paid upgrade moments — while also building the applied AI systems that make those experiences smarter. Engineers are responsible for end-to-end projects from training and productionizing classifiers to identify high-intent users, personalizing value discovery, shipping contextual onboarding experiments, or wiring new AI capabilities into measurable adoption and revenue outcomes. Growth at Perplexity goes beyond incremental funnel optimization. The team sits close to the core product - we translate behavioral signals, model outputs, and fast experimentation into durable product surfaces used across consumer and enterprise workflows. You'll move fast, run many experiments in parallel, and own the outcome end-to-end. Tech Stack: TypeScript | Next.js | React | Python | PostgreSQL | Eppo | AWS 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 Design, build, and own growth surfaces across the full funnel — activation, onboarding, SEO, lifecycle, conversion, retention, and paid upgrade moments — for Computer and every P

Description In 2026, we launched Computer, the defining product for the new era of agentic AI. Millions of people now use Perplexity to transform knowledge into action, and the Integrations team builds the systems and products that let Perplexity connect to user data and workflows across multiple verticals, turning connected data into reliable, AI-powered experiences people use every day. As an engineer on the Integrations team at Perplexity, you’ll define the technical direction of products that connect Perplexity to workflows across multiple verticals and work full-stack to build these applied AI systems. You’ll move quickly, owning outcomes end-to-end, and building useful products people reach for every day. Tech Stack: TypeScript | Next.js | React | Python | PostgreSQL | Eppo | AWS 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 other’s strengths, break down silos, and give selflessly to help our colleagues deliver excellence. What you'll do Build agentic apps, features, and workflows that make Perplexity a daily driver for users. Lead vertical-specific products and AI-powered experiences like a Personal CFO and Email Assistant, turning connected data into reliable, high-impact tools people want to use every day. Own the data backbone of pipelines, infrastructure, and connectors that bring user and enterprise data to agents and products at a 99.9% reliability bar. Drive end-to-end projects across the full stack, running experiments in parallel and hill-climbing on adoption, retention, and revenue. Set technical direction, mentor engineers, and partne

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. Ensu

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. With over half a billion rides and counting, Lyft is solving hard problems in a flourishing domain with a lot of data and creative solutions in Marketplace, Mapping, Fraud, Growth and beyond. We're actively building the next-generation Machine Learning (ML) platform for low-cost, ultra-immersive transportation to improve people’s lives using modern ML with petabyte-scale data. Our Machine Learning Engineers are excited to work on these challenging problems and redefine solutions to directly impact various aspects of Lyft's primary business. As a PhD Machine Learning Engineer Intern on our Applied AI team, you'll take on an open research problem tied to product experiences used by millions of riders. Working closely with a Staff ML Engineer mentor, you'll scope the problem, develop and evaluate new methods on real data, and take the work far enough that it can be shared with the research community, with the goal of a paper submission to a top ML venue. If you are a PhD student who enjoys turning open-ended research questions into working systems, and you want your research to be tested against real users and real data, this opportunity is for you! Responsibilities: Own a research project from start to finish: frame the problem, review related work, propose new methods, and design rigorous offline and online evaluations Design, build, train and test ML models in areas such as reinforcement learning, sequential decision-making, personalization Write production-quality code that turns research prototypes into working pipelines on Lyft's data and ML infrastructure Partner with Product Managers, Data Scientists, and fellow ML Engineers to frame research questions within the business context Analyze experimental and observational data, and communicate findings clearly to both technical and non-technical aud

About the Role The Enterprise Knowledge Platform team builds the data layer that lets Perplexity's agents reach into the world's software. This team owns the systems that turn hundreds of heterogeneous integrations (native, MCP, CLI, first-party, and third-party APIs) into one unified, reliable, well-typed surface that agents can call with confidence. This platform is the core layer that forms the knowledge layer for Computer: it is how the agent discovers what tools exist, understands what each one means, decides which to call, and grounds its reasoning in real, permissioned, up-to-date enterprise data. We maintain a knowledge layer above connectors that pushes and pulls context into them, rather than letting each connector hoard org knowledge on its own, making Computer the source of truth for institutional knowledge. Models are commoditizing; grounded, actionable, permissioned access to a customer's real systems is not. When this layer is fast, accurate, and semantically rich, every agent built on top of it gets smarter; when it is weak, no amount of model quality compensates. Key Responsibilities Own the design and implementation of the connector runtime, the system that registers, hosts, and executes built-in connectors, hosted MCP servers, and CLI-backed tools behind a single agent-facing interface. Build and extend the semantic layer: tool and entity schemas, capability metadata, relationship modeling, and the mechanisms for capturing and applying organization- and account-specific corrections and knowledge. Design the tool-discovery and tool-selection surfaces that agents use to find the right connector and call it correctly, optimizing for both model accuracy and context efficiency. Make agent loops robust: structured results, partial-failure and retry semantics, idempotency, pagination, rate-limit handling, and observability into every tool call an agent makes. Define authentication, authorization, and credential-isolation patterns for connectors (OAuth fl