Senior Lead AI Software Engineer

Klaviyo Klaviyo · Enterprise · Boston, MA · Engineering

Senior Lead AI Software Engineer role focused on building internal AI-powered automation, systems, and agents to improve internal operational efficiency. The role involves defining technical roadmaps, leading end-to-end initiatives, making architectural decisions, establishing standards for AI-native engineering, and influencing broader engineering practices. Key responsibilities include developing agentic workflows, RAG pipelines, and evaluation harnesses, while also owning system health, reliability, and operational standards.

What you'd actually do

  1. Independently own and drive high-impact objectives that span multiple Amplify teams and align with company priorities, defining the technical roadmap that ensures our internal applications, APIs, data and event pipelines, and AI-powered workflows can scale with Klaviyo and continue delivering measurable business outcomes.
  2. Be accountable, in partnership with Engineering Managers, for the long-term technical health of Amplify’s systems — quality, reliability, scalability, cost, and security — across a significant slice of Klaviyo engineering, maintaining strong system-level thinking across interconnected internal platforms.
  3. Independently lead the end-to-end lifecycle of large, multi-team initiatives with clear technical direction, architectural leadership, and active workstream curation, from discovery and design through implementation, rollout, and long-term ownership of complex programs that span internal customers across the company.
  4. Make high-judgment architectural calls in ambiguous situations, committing decisively even when facing disagreement, and use prototypes and reference implementations to de-risk decisions before broader investment.
  5. Establish shared standards, patterns, and reference implementations that multiply team effectiveness across Amplify and adjacent engineering teams, and proactively redirect efforts away from low-leverage approaches and toward higher-impact solutions when projects are off-course.

Skills

Required

  • software development
  • computer science fundamentals
  • domain-driven design
  • architectural patterns for distributed, multi-tenant systems
  • AI tools
  • coding assistants
  • agentic workflows
  • RAG pipelines
  • evaluation harnesses
  • building AI-powered systems responsibly
  • technical roadmap definition
  • architectural leadership
  • system-level thinking
  • operational standards (SLOs, monitoring, incident response, security, observability, cost)

Nice to have

  • BA or BS Degree in Computer Science, related field, or equivalent experience

What the JD emphasized

  • own hard problems end-to-end
  • drive engineering excellence
  • highly visible
  • direct impact
  • own and drive high-impact objectives
  • long-term technical health
  • lead the end-to-end lifecycle
  • architectural leadership
  • high-judgment architectural calls
  • ambiguous situations
  • Establish shared standards
  • forward-looking technical strategy
  • influence the roadmaps
  • AI-native engineering
  • agentic workflows
  • RAG pipelines
  • evaluation harnesses
  • building AI-powered systems responsibly
  • own the response to complex performance, scalability, and reliability issues
  • owning mistakes
  • Define and own the operational standards
  • Get work done primarily through influence, delegation, and clarity
  • Invest in the growth of engineers
  • Connect technical work to customer outcomes and business objectives

Other signals

  • AI-powered automation
  • AI systems and agents
  • AI-driven systems
  • AI-native engineering
  • agentic workflows
  • RAG pipelines
  • evaluation harnesses