Lead People Systems Engineer

Overview

Klaviyo is building an AI-first company—and that starts with how we support and scale our people. We are looking for a Lead People Technology Engineer to be the first dedicated AI engineer within our People Technology (KPPL) team.

Responsibilities

• AI-First People Systems & Architecture
• Reimagine core People workflows through an AI-first lens, not just incremental automation
• Design and build AI-powered workflows, copilots, and agents that automate and augment People processes across the employee lifecycle
• Architect and implement systems that integrate across SaaS such as Workday, Greenhouse, Sana, and internal Klaviyo platforms
• Partner with our internal IT AI team and establish best practices for:
• Prompt engineering and evaluation
• LLM system design and orchestration
• Versioning, testing, security, and observability of AI systems
• Enable AI Use Cases (copilots, assistants, automated workflows) that drive faster execution and better decision-making for People teams
• Collaborate with stakeholders to translate business problems into scalable AI solutions
• Driving an AI-First Operating Model
• Identify high-leverage opportunities to replace manual workflows with AI-native solutions
• Define and track success metrics tied to efficiency gains, time savings, and operational effectiveness
• Help the People organization shift toward AI-augmented ways of working
• Act as a thought partner to People leadership on what’s possible with AI, not just what’s requested
• Responsible AI, Privacy & Governance
• Design systems that handle sensitive employee data with security, privacy, and trust at the core
• Partner with Security, Legal, and Global IT to ensure compliant and ethical AI deployment
• Cross-Functional Collaboration & Enablement
• Work closely with Security, IT, and GTM Systems to align on shared AI infrastructure and standards
• Contribute to and adopt company-wide AI patterns, tooling, and best practices
• Enable People teams to leverage AI by building:
• Reusable frameworks and workflows
• Playbooks and training materials
• Help non-technical stakeholders confidently use and iterate on AI-powered tools
• Technical Leadership
• Advocate for scalable, well-governed AI systems that integrate cleanly into Klaviyo’s broader tech ecosystem
• Act as a key voice in shaping how Klaviyo becomes AI-first internally, starting with People systems

Requirements

• Passion and Curiosity to experiment and reimagine People workflows
• 5+ years of engineering or data engineering experience, with 2+ years building AI/ML or LLM-powered delivering tangible business outcomes
• Proven ability to set technical direction and build 0→1 systems with meaningful organizational impact
• Strong experience with but not limited to:
• Python, SQL, and modern APIs
• LLM platforms (OpenAI, Claude, Gemini, etc.)
• LangChain and LangGraph
• Designing AI-powered workflows, agents, or copilots
• Experience integrating with enterprise SaaS systems (HRIS, ATS, etc.)
• Experience designing scalable systems, automation frameworks, and internal tools
• Experience working with sensitive data and implementing responsible AI practices
• Strong ability to translate ambiguous business problems into scalable technical solutions

Bonus Points

• Experience with People/HR systems (Workday, Greenhouse, Sana)
• Familiarity with workflow automation platforms (e.g., n8n, Workato, Zapier)
• Experience in high-growth SaaS environments
• Contributions to AI governance, internal AI platforms, or experimentation frameworks

Qualifications

• Master's degree in Computer Science, Data Science, Engineering, or related field
• Experience with AI/ML platforms and tools
• Experience with enterprise SaaS systems and integrations
• Experience with cloud-based services (AWS, Azure, GCP)
• Experience with DevOps practices and tools
• Experience with version control systems (Git)
• Experience with CI/CD pipelines
• Experience with data modeling and analysis
• Experience with natural language processing (NLP)
• Experience with machine learning algorithms and models
• Experience with data visualization tools
• Experience with data warehousing and ETL processes
• Experience with database management systems (SQL, NoSQL)
• Experience with API development and integration
• Experience with software development methodologies (Agile, Scrum)
• Experience with project management tools (Jira, Trello)
• Experience with security and compliance practices
• Experience with ethical AI principles and practices
• Experience with user interface design and prototyping
• Experience with accessibility and inclusive design principles
• Experience with agile methodologies and practices
• Experience with continuous integration and delivery (CI/CD)
• Experience with data science and machine learning
• Experience with distributed systems and microservices
• Experience with cloud computing and infrastructure as code
• Experience with data analytics and reporting
• Experience with data visualization and storytelling
• Experience with data engineering and data pipelines
• Experience with data storage and retrieval
• Experience with data modeling and normalization
• Experience with data quality and validation
• Experience with data security and privacy
• Experience with data governance and compliance
• Experience with data warehousing and ETL processes
• Experience with data warehousing and BI tools
• Experience with data warehousing and data modeling
• Experience with data warehousing and data visualization
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