Sr. Lead Solution Architect - AI Agents

KlaviyoSan Francisco, CA
4d

About The Position

Klaviyo is revolutionizing customer experience with our new AI-powered Customer Agent Platform—a sophisticated multi-agent system designed to autonomously resolve complex customer requests end-to-end. While our initial deployments heavily index on transforming Customer Experience (CX) and Support operations, this platform will rapidly expand to encompass a wide array of brand-specific, revenue-generating, and operational use cases. In this role, you will act as the tip of the spear for this new technology, reporting directly to the VP of Global Services. You will own the hands-on execution of our most complex AI agent builds for strategic customers, acting as part Forward-Deployed AI Engineer, part Operations Strategy Consultant, and part Enablement Leader. You will work directly with outcome-obsessed enterprise leaders—proving our platform can understand their complex taxonomies and safely execute real workflows—while partnering closely with internal Product and Engineering to shape the platform's evolution. This is a senior individual contributor role (equivalent in leveling to a Sr. Manager) for someone who thrives in the ambiguity of early-stage product delivery. You must natively speak the language of business operations and CX, enjoy shipping customer-facing technical work, and possess a deep understanding of LLMs and agentic primitives.

Requirements

  • 8-10+ years in technical, customer-facing roles such as solutions architecture, forward-deployed engineering, technical consulting, or similar.
  • Proven experience operating autonomously at a Sr. Manager/Director equivalent level, delivering production-grade enterprise solutions that require structured execution, testing, and iteration.
  • Track record of working directly with senior technical stakeholders, VP-level Support/CX Leaders, and IT Operations in complex enterprise environments.
  • Strong technical foundation in API & Integration Mastery (REST, webhooks, JSON). You are comfortable building Custom Tools that connect an LLM to bespoke backend systems.
  • System of Record & Workflow Expertise. You have hands-on experience configuring and integrating with complex enterprise platforms (e.g., Zendesk, Salesforce, Shopify, ERPs) and understand how to map AI actions to traditional triggers and automations.
  • Deep conceptual understanding of Agentic AI Fundamentals. You know the difference between a traditional deterministic chatbot and an LLM-powered multi-agent system, and understand Retrieval-Augmented Generation (RAG) concepts.
  • You speak "Support & CX." You are deeply fluent in deflection vs. resolution rates, cost-to-serve, CSAT/NPS, and quality assurance frameworks.
  • Able to translate ambiguous customer needs into clear, deterministic implementation plans (Procedures) and drive execution against timelines.
  • Clear, confident communicator who can explain AI reasoning, hallucinations, and tool-calling sequencing to both technical and non-technical audiences.
  • Highly proactive, detail-oriented executor who takes ownership of outcomes and thrives in an incubation-style role.
  • Thrives in fast-moving environments with rapidly evolving K:Agent product capabilities.
  • Balances speed with rigor, utilizing simulations and tracing to ensure safety, compliance, and reliability are never compromised.

Nice To Haves

  • Hands-on experience building with or around LLMs, OpenAI's Agent SDK, LangChain, or similar orchestration frameworks.
  • Strong product instincts, including the ability to define success metrics and contribute field insight directly into product roadmap discussions.
  • A Computer Science, Engineering, or Math degree, or equivalent hands-on technical experience.

Responsibilities

  • Own end-to-end delivery of multi-agent implementations for enterprise customers, serving as the incubation leader for this capability.
  • Operate as a trusted technical partner to CX Directors, Ecommerce leaders, and IT Operations, leading through ambiguity and complexity.
  • Combine hands-on technical execution—configuring Agents, Procedures, and Custom Tools—with consultative delivery and strong stakeholder management.
  • Shape and scope AI agent engagements
  • Partner with customers and internal teams to define success criteria, scope agent builds, and translate messy, real-world business requirements into clear delivery plans.
  • Lead technical discovery conversations to map out a brand's complex support taxonomies, ensuring our system’s Router can accurately evaluate customer intent.
  • Identify risks early, clarify dependencies, and ensure alignment between customer expectations and our AI capabilities.
  • Lead end-to-end technical execution
  • Own the design, description, and configuration of specialized Agents (Skills) from initial setup through launch and post-launch iteration.
  • Write, maintain, and evolve key agent-building artifacts, specifically translating business rules into structured Procedures (deterministic workflows) and Guidance (brand tone and compliance guardrails).
  • Set up, test, and validate Custom Tools (Data and Action types) to connect the AI to external systems (Shopify, ERPs, CDPs, Loyalty platforms) so the agent can execute tasks autonomously (e.g., create_return, redeem_reward).
  • Rigorously test custom agents using our Simulation framework and Telemetry/Tracing to ensure agents meet enterprise standards for performance, safety, compliance, and scalability.
  • Act as a strategic technical advisor
  • Serve as the primary technical point of contact for customers during high-stakes agent build engagements.
  • Orchestrate the enterprise ecosystem by connecting our Customer Agent tightly to critical systems of record (e.g., Helpdesks, Commerce Platforms).
  • Map AI actions to standard routing and backend automations so they function seamlessly.
  • Drive the KPI story by building reporting frameworks that track deflection rates and resolution quality, translating metrics into CFO-friendly terms (e.g., FTE capacity savings).
  • Troubleshoot complex technical issues with urgency and precision, especially during critical customer moments.
  • Drive repeatable, scalable delivery
  • Approach each engagement with a builder’s mindset: solve the customer problem deeply, then build the standard operating procedures and architecture templates to standardize delivery.
  • Partner tightly with K:Agent Product and Engineering to surface platform gaps and influence the evolution of the Data Model (Ontology layer) and Custom Tools.
  • Contribute to internal best practices, templates, and delivery processes that improve build quality and consistency across customers.
  • Maintain strong operational hygiene, including clear documentation, status tracking, and handoffs, without requiring management oversight.
  • Lead through influence and collaboration
  • Work cross-functionally with Agent PMs, Engineering, Design, and GTM teams to deliver consistent, high-quality agent builds.
  • Demonstrate executive presence in customer interactions, effectively communicating complex AI concepts to both technical and non-technical C-suite audiences.
  • Enable the organization by training, mentoring, and sharing learnings with the broader Solution Architect team, turning your incubation learnings into a repeatable global motion.
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