Sr. Software Engineer, AI Enablement

Klaviyo Klaviyo · Enterprise · Boston, MA · Engineering

Senior Software Engineer focused on AI Enablement, building full-stack platforms and tools to integrate AI capabilities into software engineering workflows, automating processes like code generation and testing to improve engineering velocity and quality.

What you'd actually do

  1. Act as a subject matter expert for AI-driven engineering tools, mentoring other engineers and championing a culture of AI-first development.
  2. Continuously experiment with AI tools—testing, learning, and sharing insights to keep the team and organization ahead of the curve, as well as championing new applications that accelerate workflows and elevate quality responsibly.
  3. Design, implement, and maintain robust, scalable full-stack platforms and tools that allow other engineers to easily integrate and utilize AI services and capabilities within their projects.
  4. Identify high-leverage opportunities to apply AI for automating engineering processes, such as code generation, testing, deployment, and operational tasks, to dramatically improve engineering efficiency and velocity.
  5. Apply and contribute to the standards, patterns, and architectural guidance for responsible and effective AI enablement, ensuring reliability, security, and performance.

Skills

Required

  • 5+ years of full stack development experience
  • Hands-on experience with one or more front end technologies (React, TypeScript, Angular, Vue, etc.)
  • Strong experience with specific AI/ML frameworks or platforms (e.g., PyTorch, TensorFlow, LangChain, Claude, Gemini, Copilot)
  • Prior experience in a high-growth environment, navigating technical complexity and change
  • Experience with Python / Django or similarly typed languages
  • Experience with designing and managing scalable databases
  • Experience building and maintaining complex software
  • Strong experience with AWS services, how to stand up infrastructure, and monitor for defects
  • Hands-on experience with building REST APIs, GraphQL, and other middleware development tools
  • Experimented with AI in work or personal projects
  • Excited to dive in and learn fast
  • Hungry to responsibly explore new AI tools and workflows

Nice to have

  • Braintrust
  • Chronosphere
  • Cursor
  • Celery
  • Pulsar
  • Kubernetes
  • Terraform

What the JD emphasized

  • AI for software engineering
  • full-stack platforms and tools
  • automating engineering processes
  • generative AI and ML

Other signals

  • AI for software engineering
  • full-stack platforms and tools for AI integration
  • automating engineering processes with AI
  • generative AI and ML for engineering productivity