Software Engineer, Intelligence

Sierra Sierra · AI Frontier · San Francisco, CA · Engineering

Software Engineer, Intelligence role focused on building the intelligence layer for a platform that helps businesses build customer experiences with AI. Responsibilities include analyzing agent interactions, generating insights, enabling evaluation and experimentation, and developing learning systems for retrieval, ranking, personalization, and feedback loops.

What you'd actually do

  1. Build the Intelligence layer at Sierra. You’ll work on systems that analyze millions of agent interactions and generate insights that improve agent performance and customer outcomes.
  2. Turn conversations into insights. You’ll build systems for analyzing, clustering, and exploring large-scale conversational data.
  3. Enable evaluation and experimentation. You’ll design systems that allow us and our customers to measure agent quality and run experiments.
  4. Develop learning systems. You’ll work on retrieval, ranking, personalization, and feedback loops that make agents more effective over time.

Skills

Required

  • Strong software engineering fundamentals
  • experience building production systems
  • Experience working with data systems, analytics, or machine learning-driven products
  • Motivation and high-agency
  • 4+ years hands-on experience building production systems or data products
  • Degree in Computer Science or related field, or equivalent professional experience

Nice to have

  • Experience with retrieval, ranking, or recommendation systems
  • Experience building analytics or data exploration tools
  • Experience working with large-scale data systems
  • Experience building AI-powered products

What the JD emphasized

  • production systems
  • large-scale conversational data
  • measure agent quality
  • retrieval, ranking, personalization, and feedback loops
  • 4+ years hands-on experience building production systems or data products

Other signals

  • Analyze millions of agent interactions
  • Generate insights that improve agent performance
  • Build systems for analyzing, clustering, and exploring large-scale conversational data
  • Design systems that allow us and our customers to measure agent quality and run experiments
  • Develop learning systems for retrieval, ranking, personalization, and feedback loops