Member of Technical Staff (Software Engineer, Acceleration)
San Francisco • FullTime
Posted 16d ago
Remote Work Policy
On-site
Employment Type
FullTime
Categories
Applied AI Engineer
About the job
Perplexity is seeking creative, AI-pilled engineers to join our Acceleration team. This role is focused on continually improving how the company and its teams operate, aiming for order-of-magnitude improvements in product and user experience. You will ensure Perplexity makes the best use of AI tools and agents to multiply the leverage of its lean, mission-focused teams, impacting everything from frontend and backend engineering to applied AI research and business operations. The ideal candidate will have sound technical judgment from internet-scale companies, a voracious use of advanced AI tools/models, and the imagination to rethink how work gets done. This is a hands-on role expected to build prototypes and production systems, and reengineer codebases, infrastructure, and processes.
Responsibilities
- Identify, prioritize, and execute opportunities to accelerate delivery cadence with frontier AI capabilities.
- Develop empathy for technical and business teams' work to collaborate on harnessing AI.
- Make codebases, systems, and knowledge stores legible to AI.
- Help optimize the quality-velocity trade-off using AI tools and agents.
- Stay updated on new AI tools/models and effectively use them, inspiring others.
- Assist the company in making high-conviction technology bets.
- Work with leadership to instill an AI-forward culture and hire suitable candidates.
Requirements
- 5 to 15+ years of industry experience, with a focus on infrastructure/platform engineering or developer acceleration in complex environments.
- Daily use of AI models/tools with a strong understanding of their limitations.
- Proficiency with Python, and experience/desire to learn Rust, TypeScript, Go.
- Strong understanding of and empathy for technical staff's work, with enthusiasm to learn about business and operations.
- Broad working knowledge of typical stacks in AI product & applied research companies (e.g., understanding CUDA's purpose and application).
- Obsession with improving software and human-orchestrated process legibility and reducing brittleness.
- Experience navigating exploration-exploitation trade-offs, balancing immediate shipping with future capacity building.