Software Engineer Intern

Cresta Cresta · Vertical AI · Toronto Canada

Software Engineer Intern role focused on building real-time, AI-driven customer interaction systems for contact centers. The role involves working on production infrastructure for AI agents, real-time assistance, conversation intelligence, and evaluation systems, with an emphasis on low latency, reliability, and business outcomes.

What you'd actually do

  1. Design and build systems that support real-time AI-powered customer interactions
  2. Work on features combining LLMs, data systems, and user-facing applications
  3. Collaborate with engineers, product, and ML teams to ship production-ready solutions
  4. Build systems for evaluation, monitoring, and continuous improvement of AI behavior
  5. Optimize for low latency, high throughput, and reliability at scale

Skills

Required

  • Experience with one or more programming languages (e.g., Python, Go, Java, JavaScript, TypeScript)
  • Interest in building user-facing products, backend systems, or real-time/data-intensive applications
  • Familiarity with modern web development (frontend and/or backend), APIs, or system design fundamentals
  • Understanding of building reliable, maintainable systems
  • Curiosity about LLMs, AI agents, or production AI systems

Nice to have

  • Experience using AI-powered developer tools (e.g., Cursor, Claude Code) to accelerate development workflows
  • Strong proficiency in agentic coding workflows—effectively collaborating with AI tools to design, implement, and iterate—is a strong plus
  • A driver mindset—you proactively identify problems, take initiative, and push work forward rather than waiting for direction

What the JD emphasized

  • systems that power real-time, AI-driven customer interactions in contact centers
  • live production environments
  • AI Agents & Automation
  • Real-Time Agent Assist
  • Conversation Intelligence
  • AI Evaluation & Reliability
  • Platform & Infrastructure
  • real-time AI-powered customer interactions
  • LLMs, data systems, and user-facing applications
  • evaluation, monitoring, and continuous improvement of AI behavior
  • low latency, high throughput, and reliability at scale
  • Take ownership of problems end-to-end—from identifying gaps to shipping solutions
  • building reliable, maintainable systems
  • Curiosity about LLMs, AI agents, or production AI systems
  • Strong proficiency in agentic coding workflows—effectively collaborating with AI tools to design, implement, and iterate—is a strong plus
  • A driver mindset—you proactively identify problems, take initiative, and push work forward rather than waiting for direction
  • build and ship production-grade AI systems
  • design systems balancing model quality, latency, and reliability
  • AI agents are deployed, evaluated, and improved at scale
  • AI-driven operations
  • AI in production
  • Hybrid workforce
  • Real business impact
  • Driver culture
  • Ownership & velocity
  • own real problems, ship quickly, and work at the frontier of applied AI

Other signals

  • AI Agents & Automation
  • Real-Time Agent Assist
  • Conversation Intelligence
  • AI Evaluation & Reliability
  • Platform & Infrastructure