Member of Technical Staff (Applied AI Engineer, Agent Capabilities)

Perplexity
San Francisco, New York
Workplace: OnsiteFull timeUSD 220,000 - 405,000 annuallyFunction: Data Science & Machine LearningExperience: 6+ yearsSkills: ["Product judgment","Technical leadership","Ownership","Collaboration","Design review"]

Build and productionize agent capabilities by evaluating frontier models on real user tasks, identifying failure modes, and turning the best advances into reliable agent systems. Improve agent planning, tool use, context handling, and long-running execution, using ML/LLM techniques to design scalable capabilities (skills, plugins, auto-research, multi-agent collaboration). Own agent behavior end-to-end with rigorous evaluations, monitoring, and secure, observable infrastructure.

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FursaFursa
Perplexity
Perplexity
3 days ago

Member of Technical Staff (Applied AI Engineer, Agent Capabilities)

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 16 hours agoStatus: Live

Job Summary

Build and productionize agent capabilities by evaluating frontier models on real user tasks, identifying failure modes, and turning the best advances into reliable agent systems. Improve agent planning, tool use, context handling, and long-running execution, using ML/LLM techniques to design scalable capabilities (skills, plugins, auto-research, multi-agent collaboration). Own agent behavior end-to-end with rigorous evaluations, monitoring, and secure, observable infrastructure.
Location: San Francisco, New York
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Evaluate frontier models against real user tasks, identify useful behaviors and failure modes, and turn promising advances into production agent systems from prototype to launch and iteration.
  • •Improve agents’ planning, tool use, context management, error recovery, and reliability for long-running tasks.
  • •Design scalable agent capabilities using state-of-the-art ML/LLM techniques (e.g., skills, plugins, artifact generation, tool integration, auto-research, and multi-agent collaboration).
  • •Own agent behavior and capabilities end-to-end, defining offline/online evaluations for task completion, correctness, safety, latency, cost, and user satisfaction.
  • •Build secure, observable, and reliable agent systems with permissions/safeguards and tracing, replay, and monitoring infrastructure.

Pay and Benefits

Salary: USD 220,000 - 405,000 annually
Equity and Bonus:Equity

Key Requirements

  • •Typically 6+ years of professional software engineering experience, with a track record of building and owning robust AI/ML-powered, large-scale products.
  • •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 rigorous evaluation, production monitoring, and iterative improvement using metrics and user feedback.
  • •Practical experience in one or more areas such as agent harnesses, tool use, context engineering, model evaluation, browser automation, or long-running task execution.
  • •Strong product judgment to translate ambiguous user needs into applied AI/ML problems and ship measurable solutions.
Experience:6+ yearsAI/MLAgentic AILLMsDistributed systems
Skills:Product judgmentTechnical leadershipOwnershipCollaborationDesign review
Tech Stack:PythonGoRustPostgreSQLDynamoDBAWSTypeScript

Company Brief

Perplexity
Perplexity AI provides an AI-powered answer engine that returns conversational, citation-backed answers to user queries and offers Pro/Enterprise products and APIs for research, knowledge work, and search augmentation.
Industry: AI & Machine Learning
Company Size: Medium (51 to 250 employees)
Revenue: USD 50M to 100M
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series D
Headquarters: San Francisco, United States
Founded: 2022
Glassdoor
Glassdoor: 4.6
WebsiteLinkedInGlassdoor