Build systems: Lead engineers and operations to design and build automated systems and internal tools that make customer success responsive and high-quality. Decide when to leverage external software and how to connect with internal systems
Streamline processes: As AI advances, we will need fewer manual steps, better workflows, and more powerful tools that will allow individuals to own larger scope and work on a higher strategic level
Accumulate knowledge: Develop onboarding, training, support processes, help center content, and knowledge bases, leveling up the team’s knowledge while raising the bar for quality
Gather data: Track key metrics like response times, resolution rates, and customer satisfaction. Use both quantitative and qualitative data to iteratively guide improvements.
Scale: Ensure that internal systems and teams can scale as our user base grows
Pre-sales: Develop compelling technical demos that accurately communicate a breadth and depth of product features. Communicate the qualitative and quantitative value of a rapidly changing product
Post-sales: Leading integration and technical debugging, end-user training, and gathering customer feedback iteratively
5+ years in solutions engineering, customer success, or related general management roles, with demonstrated cross-functional leadership
Experience leading solutions engineering and operations teams
Strong track record of designing and implementing automated systems that improve efficiency
Experience working with engineers to scope, build, and deploy solutions
Skilled at adapting operational challenges into scalable solutions
Hands-on approach: able to analyze details and resolve issues as needed
Prepare for your Solutions Engineering Lead interview at Perplexity AI.
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