Member of Technical Staff (Software Engineer, Agent Capabilities)

Навыки

• AI-агенты
• AWS
• Распределённые системы
• Лидерство
• LLM
• Machine Learning
• Ответственность за результат

О компании и продукте

• 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 every action an agent takes is metered, budgeted, and settled through the billing platform this role owns.
• 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 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 Capabilities team is responsible for turning frontier AI breakthroughs into reusable product capabilities. We are often the first to evaluate emerging model capabilities, define how they should appear in the product, and transform them into reliable, production grade 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.
• Craftsmanship. We build high quality, tasteful products targeting both the AI native and AI curious.

Задачи

• Investigate emerging frontier-model behaviors and identify opportunities to turn them into product capabilities
• Help define how advances in reasoning, planning, memory, learning, and agent collaboration appear in the product
• Build and evolve Skills, Workflows, and Artifacts into a coherent ecosystem
• Shape the architecture, abstractions, and product experiences that enable both users and agents to compose increasingly sophisticated solutions for complex real-world tasks
• Own capabilities end-to-end, from user-facing products and interfaces to backend services, evaluation, data models, and production operations
• Build scalable platform infrastructure and backend systems that power capability execution, sharing, and lifecycle management across high volume user and agent interactions
• Collaborate closely with PM, Design, Data Science, Sales, Research, to identify high-impact opportunities in both consumer and enterprise customer experiences, validate emerging capabilities, and translate complex agent behaviors into simple, reliable product experiences
• Set technical direction on ambiguous problems and raise the bar through design reviews, mentorship, and technical leadership

Требования

• Typically 8+ years of professional software engineering experience, with a track record of owning and delivering complex products or systems from conception to production
• Strong full-stack engineering fundamentals, including experience building user-facing products, backend services, and scalable distributed systems that serve high traffic and large user bases
• Strong product judgment and instincts
• you turn vague needs into simple, reliable systems and ship without waiting for perfect specs
• Comfort with data-informed decisions
• you define the metrics and evals that prove a system works, and iterate on them
• Experience designing abstractions, platforms, or reusable systems that enable other engineers, users, or automated systems to accomplish complex tasks
• Strong execution: you can take ambiguous product needs, break them down, and ship durable systems with clear user impact
• Genuine interest in frontier AI capabilities, agent systems, and excitement for rapidly exploring, evaluating, and productizing new model behaviors

Будет плюсом

• Experience building agentic systems (tool calling, subagents, long-running or autonomous task execution)
• Experience building developer platforms or reusable-capability primitives (SDKs, plugin systems, workflow engines)
• Experience with evaluation, benchmarking, or quality systems for ML/LLM-powered products
• Time spent at a fast-growing startup or on a high-ownership engineering team

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