Engineering Manager for AI Inference team focused on building and scaling the infrastructure for Perplexity's AI capabilities, including deploying and optimizing large sparse/MoE models, developing inference APIs, and improving system reliability and observability.

AI Infrastructure Engineer responsible for building, deploying, and optimizing large-scale AI training and inference clusters using Kubernetes and Slurm on AWS. The role involves managing HPC environments, developing orchestration systems, implementing resource scheduling, and building monitoring solutions for ML workloads.

Perplexity is looking for an AI Software Engineer to join their Agents team, focusing on building agentic experiences within their AI products. The role involves designing AI agents, training action/decision models, ensuring excellent user experiences across platforms, developing secure agentic capabilities, and optimizing data representations for agent-environment interaction. The engineer will drive AI capabilities, leverage AI models and infrastructure, and ensure high quality in AI agent performance and user experience.

The Model Behavior Architect will design and optimize context engineering strategies and evaluation systems for Perplexity's AI products. This role involves pressure-testing model capabilities, ensuring behavioral consistency, and supporting model launches by identifying and fixing failure modes. The goal is to deliver high-quality user experiences by improving model behavior and quality through systematic evaluation and iteration.

Applied AI Engineer to design, build, and iterate on cutting-edge agents powering the core experience in Perplexity Computer. This role involves developing frontier context layer applications, personalization, recommendations, and monetization applications, as well as building agent capabilities. The engineer will own the full model lifecycle from research to production, including data analysis, modeling, evaluation, A/B testing, and iterative improvement, and will also build an auto research harness for agent exploration. Collaboration with cross-functional teams and staying updated on AI innovation are key.

This role is for a software engineer on the 'Computer' team at Perplexity, focusing on building and owning product and platform systems for agentic AI. The engineer will lead features end-to-end, iterate on hard problems, and build systems that handle AI nuances like agents, context, evaluation, and personalization. The role requires strong software engineering experience, production system building, and product judgment, with a preference for experience in LLMs, agents, retrieval systems, personalization, or evaluation frameworks.

AI Inference Engineer responsible for building and running the inference engine for Perplexity's models, focusing on performance, latency, and cost optimization across various model architectures. The role involves supporting transformer-based models, migrating GPU kernels, developing a Rust-native serving runtime, and ensuring reliability and observability of the inference infrastructure.

Software Engineer to build AI Foundation & Platform, focusing on end-to-end AI data, evaluation, and personalization infrastructure for agent products. Responsibilities include designing scalable data pipelines, high-performance infrastructure for personalization features, and a multi-modal evaluation platform. Requires strong programming, data engineering, and distributed systems experience, with familiarity in cloud services and ML/AI engineering support.

AI Security Engineer responsible for designing and implementing mechanisms to secure AI systems, including LLM APIs, agents, and self-hosted models, against adversarial threats. This involves hands-on remediation, threat modeling, and security assessments.

This role focuses on building AI systems to revolutionize data science workflows. The core responsibilities include developing AI agents for autonomous data analysis, making data warehouses AI-readable, automating data lifecycle management with self-healing pipelines, and creating AI-powered experiment analysis tools. The goal is to transform the data team into an AI-native product team, enabling significant leverage and industry-leading practices.

This role focuses on building AI systems to revolutionize how data science is performed. The core responsibilities include developing AI agents for autonomous data analysis (hypothesis generation, query execution, interpretation, recommendations), making the data warehouse AI-readable, automating data lifecycle management with self-healing pipelines, and creating AI-powered experiment analysis tools. The goal is to transform the data team into a product team by building internal data products that leverage AI, enabling 10x operational efficiency.

Forward Deployed Engineer role focused on integrating Perplexity's AI API Platform and Perplexity Computer (agentic workflows) into enterprise customer systems. The role involves designing, building, and deploying end-to-end AI integrations, automating business workflows, and optimizing performance, security, and customer impact. Requires strong software engineering skills, experience with LLM-powered systems, and customer-facing deployment.

This role focuses on leveraging AI tools and agents to improve the efficiency and delivery cadence of various teams within Perplexity, including engineering, research, and operations. The candidate will be responsible for identifying opportunities to use AI, making internal systems AI-legible, and building both prototypes and production systems to accelerate development and operations. It's a hybrid role blending AI product development, infrastructure/platform engineering, and developer experience.