Solutions Architect

About Pinecone

Pinecone is pioneering a vector database to power modern AI/ML applications. We provide customers with capabilities that until now have only been in the hands of a few tech giants. Our team & investors previously launched Amazon SageMaker, built infra at Google & Facebook, ran ML platforms at Splunk, and acted as Snowflake, Elastic and Couchbase executives. Pinecone is growing fast and is funded by top tier VCs. If you have an entrepreneurial mindset and want to be an early part of Pinecone’s growth, this is the opportunity for you.

About the Role

As our Solutions Architect, you will help customers use and expand the usage of Pinecone and help them realize value from Pinecone faster. You will lead technical discussions with customers about Pinecone, their use cases, and best practices. You will offer advice, solve technical issues, and provide technical leadership for customer POCs.

Responsibilities

  • Improve customers’ experience by providing technical support, sharing best practices, leading technical discussion, discovering use cases, delivering product demos and proof of concept to show value from Pinecone
  • Build trust and establish relationships with the customer teams, helping them realize value from Pinecone, and working backwards from optimal customer experience
  • Engage with Product teams to guide them through customer requests and provide input to the roadmap
  • Become an expert in Pinecone, Vector search, and related partner products, as customers will seek your advice and expertise

What we look for

  • 4+ years of experience in customer facing technical role (Solution Architect, Customer Success Engineer, Professional Services, Technical Support, Sales Engineer)
  • Proficiency in Python, Scala, Java, or Rust
  • Experience with databases, data warehousing, big-data, streaming, search engines, or data science
  • Experience using Cloud Infrastructure with GCP, AWS, or Azure in the areas of networks, security, orchestration, containers, microservices, and understanding of concepts like VPC peering, IAM, and role management
  • Understanding of the language and technical stacks of ML/infra engineers and data scientists
  • As the technical stacks evolve continuously, being curious and a life-long learner is a requirement
  • Strong presentation and communication skills, both verbal and writing
  • Entrepreneurial and problem-solving mindset, experience managing customer challenges and seeing them through resolution
  • Technical Bachelor's degree (Computer Science, Engineering, Mathematics)

Bonus Points

  • Experience working with search engines like Elastic, Open Search, or Lucene
  • Experience working with text processing or NLP
  • Background in Machine learning tools and services

 

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