Software Engineer, AI Product Insights

Mixpanel Mixpanel · Data AI · San Francisco, CA · Engineering

Software Engineer on the Proactive Insights team, building AI-powered features for Mixpanel's analytics platform. This involves end-to-end development from agent logic and query orchestration to frontend visualization and delivery, aiming to transform the platform into a proactive partner for users.

What you'd actually do

  1. Build AI-powered features end-to-end, from agent logic and query orchestration to frontend visualization and delivery
  2. Design and implement user experiences for surfacing automated insights: dashboards, notifications, digests, and interactive analysis flows
  3. Collaborate with Product and Design to define what proactive analytics looks like and how users interact with AI-generated insights
  4. Partner with the AI Engine team to integrate shared tooling for agent orchestration, evaluation, and observability
  5. Instrument tracking and build dashboards to measure feature adoption and the quality of AI-generated insights

Skills

Required

  • Bachelor's degree in Computer Science, Mathematics, a related field, or equivalent practical experience
  • 2 to 5+ years of professional software engineering experience
  • Strong full-stack fundamentals: you're comfortable working across frontend, backend, and data layers
  • Excellent debugging and technical investigation skills
  • Strong technical communication, ideally with experience collaborating in an asynchronous remote environment
  • Ability to move fast and iterate in ambiguous, greenfield problem spaces: you take ownership and focus on delivering value to users
  • A data-driven mindset and genuine curiosity about how people use analytics tools
  • A desire to be on the forefront of leveraging AI to drive product improvement at thousands of companies

Nice to have

  • Experience building with LLMs, AI agents, or tool-use frameworks
  • React / TypeScript experience
  • Django / Python experience
  • Familiarity with analytics or observability platforms
  • Interest in information retrieval, anomaly detection, or statistical analysis

What the JD emphasized

  • AI-first analytics vision
  • building the intelligent layer
  • AI-powered root cause analysis
  • AI automations for KPI monitoring
  • intelligent alerts and anomaly detection
  • agent logic and query orchestration
  • agent orchestration, evaluation, and observability

Other signals

  • AI-first analytics vision
  • building the intelligent layer
  • AI-powered root cause analysis
  • AI automations for KPI monitoring
  • intelligent alerts and anomaly detection
  • build AI-powered features end-to-end
  • agent logic and query orchestration
  • leveraging shared infrastructure for orchestration, evaluation, and observability