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About This Role
*At Klaviyo, we value the unique backgrounds, experiences and perspectives each Klaviyo (we call ourselves Klaviyos) brings to our workplace each and every day. We believe everyone deserves a fair shot at success and appreciate the experiences each person brings beyond the traditional job requirements. If you're a close but not exact match with the description, we hope you'll still consider applying. Want to learn more about life at Klaviyo? Visit* *klaviyo.com/careers* *to see how we empower creators to own their own destiny.*
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.
In this role, you will:
- 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.
How You'll Make a Difference
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.
Who You Are
Experience
- 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.
Technical \& Domain Skills
- 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.
Consultative \& Communication Skills
- 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.
Working Style
- 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 Have
- 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.
Get to Know Klaviyo
We're Klaviyo (pronounced clay\-vee\-oh). We empower creators to own their destiny by making first\-party data accessible and actionable like never before. We see limitless potential for the technology we're developing to nurture personalized experiences in ecommerce and beyond. To reach our goals, we need our own crew of remarkable creators—ambitious and collaborative teammates who stay focused on our north star: delighting our customers. If you're ready to do the best work of your career, where you'll be welcomed as your whole self from day one and supported with generous benefits, we hope you'll join us.
*AI fluency at Klaviyo includes responsible use of AI (including privacy, security, bias awareness, and human\-in\-the\-loop). We provide accommodations as needed.*
*By participating in Klaviyo's interview process, you acknowledge that you have read, understood, and will adhere to our* *Guidelines for using AI in the Klaviyo interview Process. For more information about how we process your personal data, see our* *Job Applicant Privacy Notice.*
*Klaviyo is committed to a policy of equal opportunity and non\-discrimination. We do not discriminate on the basis of race, ethnicity, citizenship, national origin, color, religion or religious creed, age, sex (including pregnancy), gender identity, sexual orientation, physical or mental disability, veteran or active military status, marital status, criminal record, genetics, retaliation, sexual harassment or any other characteristic protected by applicable law.*
*IMPORTANT NOTICE: Our company takes the security and privacy of job applicants very seriously. We will never ask for payment, bank details, or personal financial information as part of the application process. All our legitimate job postings can be found on our official career site. Please be cautious of job offers that come from non\-company email addresses (@klaviyo.com), instant messaging platforms, or unsolicited calls.*
By clicking "Submit Application" you consent to Klaviyo processing your Personal Data in accordance with our Job Applicant Privacy Notice. If you do not wish for Klaviyo to process your Personal Data, please do not submit an application.*You can find our Job Applicant Privacy Notice* *here* *and* *here* *(FR).*
Salary Context
This $168K-$252K range is above the median for AI Agent Developer roles in our dataset (median: $203K across 46 roles with salary data).
View full AI Agent Developer salary data →Role Details
About This Role
AI Agent Developers build autonomous systems that can reason, plan, and take actions. They design multi-step workflows, tool-use frameworks, and orchestration layers that let LLMs interact with external systems. This is the frontier of applied AI engineering.
Agent development is where the most interesting (and hardest) problems in applied AI live right now. Making an LLM answer a question is straightforward. Making it reliably execute a 15-step workflow that involves calling APIs, reading databases, making decisions, and recovering from errors is an unsolved problem. You're building systems that have to work despite the fact that the underlying model is non-deterministic.
Across the 26,159 AI roles we're tracking, AI Agent Developer positions make up 0% of the market. At Klaviyo, this role fits into their broader AI and engineering organization.
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
What the Work Looks Like
A typical week includes: designing the action space and tool definitions for a new agent use case, debugging why the agent chose the wrong action sequence on a specific input, building evaluation frameworks that test agent reliability across hundreds of scenarios, optimizing the prompt chain for cost and latency, and implementing safety guardrails to prevent the agent from taking destructive actions. The work is equal parts engineering and empirical science.
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
Skills Required
Deep experience with LLM APIs and agent frameworks (LangChain, CrewAI, AutoGen). Strong understanding of prompt engineering, function calling, and error handling for non-deterministic systems. Python is standard. Experience with orchestration patterns, state management, and workflow engines adds significant value.
The best agent developers think like systems engineers. They design for failure modes, build observability into every step, and understand that agent reliability is the product. Expertise in evaluation methodology for non-deterministic systems is the differentiator. Can you measure whether your agent works 'well enough'? Can you find the edge cases where it breaks?
Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.
Compensation Benchmarks
AI Agent Developer roles pay a median of $239,000 based on 50 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($210K) sits 12% below the category median. Disclosed range: $168K to $252K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
Klaviyo AI Hiring
Klaviyo has 8 open AI roles right now. They're hiring across AI Product Manager, AI/ML Engineer, AI Agent Developer. Positions span Boston, MA, US, Denver, CO, US, San Francisco, CA, US. Compensation range: $144K - $366K.
Location Context
AI roles in Boston pay a median of $218,900 across 268 tracked positions. That's 19% above the national median.
Career Path
Common paths into AI Agent Developer roles include Software Engineer, LLM Engineer, Prompt Engineer.
From here, career progression typically leads toward AI Architect, Principal Engineer, Head of AI Engineering.
Build agents. That's the portfolio. Take an open-source agent framework, build something that completes a non-trivial multi-step task, evaluate it rigorously, and document what you learned about reliability, cost, and failure modes. The field is new enough that practical experience counts for more than credentials.
What to Expect in Interviews
Interviews focus on systems thinking and reliability engineering. Expect questions about agent architecture: how you'd design a multi-step workflow with error recovery, how you'd evaluate agent performance, and how you'd prevent agents from taking destructive actions. Coding exercises often involve building a simple agent with tool use and evaluating its behavior across different scenarios. Discussion of safety and guardrails is increasingly common.
When evaluating opportunities: Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.
AI Hiring Overview
The AI job market has 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 roles).
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
The AI Job Market Today
The AI job market spans 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (2,416) are outnumbered by mid-level (16,247) and senior (5,153) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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