Member of Technical Staff (Software Engineer, Capabilities)
Software Engineer · Senior · Full Time
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Role
What you'll do.
Perplexity AI is seeking a highly skilled Senior Software Engineer to join their Capabilities team, focusing on developing advanced AI agent systems. The ideal candidate will drive innovation in AI product development, working on cutting-edge technologies that enable intelligent agent reasoning, skill development, and system primitives.
Responsibilities
- AI System Development: Build and own systems spanning the agent product and core engine, focusing on developing sophisticated AI capabilities
- Technical Leadership: Set technical direction for ambiguous problems, conduct design reviews, provide mentorship, and drive cross-team projects
- Agent Capability Engineering: Develop primitives for Skills, Workflows, and Artifacts to create a coherent AI agent experience
- Evaluation System Design: Create comprehensive benchmarks, evaluation frameworks, and feedback loops to ensure top-tier AI capability performance
- Model Capability Integration: Integrate new model capabilities into the product, including planning, long-running tasks, and autonomous execution
Qualifications
What we look for.
Technical
Backend Engineering
Expertise in designing and building scalable, reliable distributed systems for high-traffic applications
System Architecture
Proven ability to design complex software systems end-to-end with robust architectural principles
Education
Computer Science
Bachelor's or Master's degree in Computer Science, Software Engineering, or related technical field preferred
Experience
Professional Experience
Minimum 8 years of professional software engineering experience with proven track record of system ownership
Skills
Required
Programming Languages
Proficiency in Python, TypeScript, and Go
System Design
Advanced skills in designing scalable and reliable distributed systems
AI Product Development
Deep understanding of AI system design and agent capabilities
Preferred
Agentic Systems
Nice to haveExperience with tool calling, subagents, and autonomous task execution
ML Evaluation
Nice to haveBackground in benchmarking and quality assessment for ML/LLM-powered products
Tech stack
Languages
Frameworks
Databases
Tools
Other
Compensation
Pay and benefits.
Base·USD 220,000 – 405,000
Equity·Stock options
Benefits
Equity Compensation
Stock options providing potential additional financial upside
Innovative Work Environment
Opportunity to work at the frontier of AI technology with cutting-edge challenges
Professional Growth
High-ownership engineering team with opportunities for continuous learning and development
Process
Interview steps.
- 01
Initial Screening
Review of resume and initial qualifications by recruiting team
- 02
Technical Phone Screen
Detailed discussion of technical background and problem-solving approach
- 03
System Design Interview
In-depth evaluation of candidate's system design and architectural skills
- 04
Technical Interviews
Multiple rounds focusing on coding, AI system design, and practical problem-solving
- 05
Final Leadership Interview
Discussion with senior technical leadership about vision, approach, and team fit
Full posting
Original listing.
In 2026, we launched Computer, the Perplexity agent that turns knowledge into action. The Capabilities team builds the Skills, Workflows, and Artifacts that users and agents reuse to do better work.
As a Member of Technical Staff on the Capabilities team, you'll own systems spanning the agent product, core engine and the evaluation of Skills and Artifacts. Our goal is for Computer to be the natural place to use each new model capability as it reaches the frontier, and you'll help define how that happens.
Tech Stack: Python | Go | PostgreSQL | DynamoDB | AWS | TypeScript | React
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
Build a deep, hands-on understanding of how frontier LLMs reason and where they break, then turn that into better engine and primitive design.
Bring each new model capability into the product as it reaches the frontier, including planning, long-running tasks, autonomous execution, and self-evolving skills and agents.
Work closely with the agent engine layer (context management, tool calling, planning, long-horizon execution) to turn frontier capabilities into reliable primitives.
Design, build, and own the primitives at the heart of Computer (Skills, Workflows, and Artifacts) so they compose into one coherent experience.
Build the evaluation systems (benchmarks, evals, rubrics, feedback loops) that make each capability best-in-class before broad rollout.
Set technical direction on ambiguous problems and raise the bar through design reviews, mentorship, and example.
Qualifications
8+ years of professional software engineering experience, shipping and owning complex systems end-to-end.
Strong backend / Full Stack engineering skills, with experience in designing and building scalable and reliable distributed systems, serving high traffic and a large user base.
Demonstrated technical leadership: you scope ambiguous problems, set direction, and drive cross-team projects to durable outcomes.
Strong product judgment and ownership 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.
Genuine interest in AI products, with hands-on adoption and a willingness to learn quickly.
Nice to have
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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