Sr. Lead AI Engineer

Klaviyo Klaviyo · Enterprise · Boston, MA · Engineering

Sr. Lead AI Engineer responsible for the technical leadership, architecture, and execution of high-impact AI services and agentic systems within the AI & Analytics organization. This role involves building and hardening AI serving systems, evolving agentic architecture, setting engineering standards, and mentoring other engineers. The focus is on hands-on technical leadership for production generative and agentic AI applications.

What you'd actually do

  1. Define and improve the engineering architecture for Service and Marketing AI capabilities.
  2. Build and harden AI serving systems.
  3. Evolve our agentic architecture.
  4. Set engineering standards for AI services.
  5. Lead cross-team technical work.

Skills

Required

  • Backend engineering
  • Distributed systems
  • Generative AI
  • Agentic AI
  • LLM-backed flows
  • Tool-using agents
  • Retrieval-augmented systems
  • Prompt design
  • Few-shot approaches
  • Fine-tuning
  • Evaluation of AI systems
  • Large-scale distributed systems
  • Reliable services
  • Async processing pipelines
  • Distributed task queues
  • Python
  • FastAPI
  • Django
  • Big data tools
  • Spark
  • Hadoop
  • ORMs
  • SQLAlchemy
  • Alembic
  • AWS
  • Kubernetes
  • CI/CD pipelines
  • Observability
  • Operational best practices
  • Technical leadership
  • Architecture design
  • Cross-functional collaboration
  • Customer needs translation
  • Pragmatic decision making

Nice to have

  • Service AI
  • Marketing AI
  • Low-latency backend systems
  • APIs
  • AI serving systems
  • Orchestration
  • LLMs
  • Tools
  • Evaluators
  • Retrieval systems
  • SLOs
  • Agentic architecture
  • Tool use
  • Autonomy
  • Reliability
  • Prompt versioning
  • Model versioning
  • Offline tests
  • Online tests
  • Incident response
  • Design reviews
  • Code quality
  • Cross-team technical work
  • Product teams
  • Platform teams
  • Ownership boundaries
  • Interfaces
  • Dependencies
  • Mentoring
  • Upleveling engineers
  • Senior engineers
  • Mid-level engineers
  • System owners
  • Palo Alto hub
  • Engineering rituals
  • Hiring
  • Onboarding
  • Cross-hub collaboration
  • Metrics definition
  • Latency
  • Cost-to-serve
  • Agent success rates
  • Eval scores
  • Customer adoption
  • Roadmap decisions
  • Technical decisions
  • Engineering workflows
  • Product development workflows
  • Agentic coding tools
  • AI-first working
  • Celery
  • Kafka
  • SQS
  • RabbitMQ
  • Redis
  • High-throughput workloads

What the JD emphasized

  • Lead the design of scalable, low-latency backend systems and APIs
  • Lead the development of services that host and orchestrate AI models (LLMs, tools, evaluators, retrieval systems)
  • Drive the technical roadmap for Service and Marketing AI agents
  • Establish best practices for evaluation, safety/guardrails, prompt and model versioning, offline and online tests, and incident response for AI-backed systems
  • 8+ years of professional software engineering experience with a strong focus on backend and distributed systems
  • You’ve built and shipped generative or agentic AI applications (e.g., LLM‑backed flows, tool‑using agents, retrieval‑augmented systems) and are comfortable with prompt design, few‑shot approaches, fine‑tuning, and evaluation.
  • You’ve designed human and automated evals for AI systems, know how to instrument for quality, and understand how to balance latency, cost, and response quality in real‑world usage.
  • You’ve already been effectively practicing agentic coding in your daily work.

Other signals

  • Owns architecture and execution for complex, distributed backend systems
  • Guides other engineers through design and implementation
  • Partners closely with product, machine learning, and data science
  • Hands-on tech lead role, not a people-manager role
  • Define and improve the engineering architecture for Service and Marketing AI capabilities
  • Build and harden AI serving systems
  • Evolve our agentic architecture
  • Set engineering standards for AI services
  • Lead cross-team technical work
  • Mentor and uplevel engineers
  • Measure what matters
  • Seasoned backend engineer & tech lead
  • Hands-on with generative & agentic AI in production
  • Deep experience with large-scale distributed systems
  • Strong Python and data tooling fluency
  • Production-grade cloud experience
  • Evaluation and quality-obsessed
  • Technical leader, not just individual contributor
  • Collaborative and customer-first
  • You’ve already been effectively practicing agentic coding in your daily work