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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.*
Senior Software Engineer, AI Enablement
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Why You Should Join the AI Enablement Team
Join our dynamic AI Enablement team and play a pivotal role in accelerating our engineering organization's velocity and innovation. As a Senior Software Engineer, you'll be at the forefront of how we apply Artificial Intelligence to software engineering—building the foundational frameworks, experimenting in real production workflows, and contributing to how teams across the company build with AI. We are looking for an experienced Full Stack Engineer with a deep passion for using AI and automation to solve complex, large\-scale problems.
What You'll Achieve: Key Responsibilities
You will be the driving force behind AI adoption across our engineering teams, focusing on tangible, impactful outcomes:
- Technical Leadership: Act as a subject matter expert for AI\-driven engineering tools, mentoring other engineers and championing a culture of AI\-first development.
- Experiment: Continuously experiment with AI tools—testing, learning, and sharing insights to keep the team and organization ahead of the curve, as well as championing new applications that accelerate workflows and elevate quality responsibly.
- Build Paved Paths: Design, implement, and maintain robust, scalable full\-stack platforms and tools that allow other engineers to easily integrate and utilize AI services and capabilities within their projects.
- Drive Automation: Identify high\-leverage opportunities to apply AI for automating engineering processes, such as code generation, testing, deployment, and operational tasks, to dramatically improve engineering efficiency and velocity.
- Establish Best Practices: Apply and contribute to the standards, patterns, and architectural guidance for responsible and effective AI enablement, ensuring reliability, security, and performance.
- Cross\-Functional Collaboration: Partner closely with Product, Design, and other Engineering teams to understand needs, gather requirements, and deliver production\-ready solutions.
What Makes This Role Exciting
- Hot Start \& High Impact: You won't be on a "listening tour." Your first 90 days will involve tackling tangible projects that provide an immediate impact on engineering productivity.
- Shape the Future: You will be at the forefront of applying generative AI and ML to drive meaningful improvements to how our engineering teams work.
- Ownership and Ambition: You will have significant ownership over the tools and platforms you build, solving complex, open\-ended problems that directly contribute to our company's ambition and growth.
Who You Are:
- 5\+ years of full stack development experience.
- Hands\-on experience with one or more front end technologies (React, TypeScript, Angular, Vue, etc.)
- Strong experience with specific AI/ML frameworks or platforms (e.g., PyTorch, TensorFlow, LangChain, Claude, Gemini, Copilot).
- Prior experience in a high\-growth environment, navigating technical complexity and change.
- Experience with Python / Django or similarly typed languages.
- Experience with designing and managing scalable databases.
- Experience building and maintaining complex software. You'll join us in writing clean, maintainable software that solves hard problems. You'll write testable, quality code. You'll push the team and the mission forward with your contributions.
- Strong experience with AWS services, how to stand up infrastructure, and monitor for defects.
- Hands\-on experience with building REST APIs, GraphQL, and other middleware development tools.
- You've already experimented with AI in work or personal projects, and you're excited to dive in and learn fast. You're hungry to responsibly explore new AI tools and workflows, finding ways to make your work smarter and more efficient.
Technologies we use (not exhaustive):
- Python, Django, Celery
- Braintrust, chronosphere
- Claude, Cursor
- MySQL, Redis, Pulsar
- Amazon Web Services (EC2, RDS, Aurora, etc.), Kubernetes, Terraform, and other DevOps tools
- React, TypeScript, JavaScript, HTML, CSS
*This role may require up to 10% travel for purposes such as new hire onboarding, client or partner work if applicable, team meetings, and industry events. Travel is coordinated in advance.*
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 $148K-$222K range is below the median for AI Software Engineer roles in our dataset (median: $190K across 251 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 4,133 AI roles we're tracking, AI Software Engineer positions make up 8% of the market. At Klaviyo, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $232,000 based on 863 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($185K) sits 20% below the category median. Disclosed range: $148K to $222K.
Across all AI roles, the market median is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Safety ($274,200) and AI Engineering Manager ($268,700). By seniority level: Entry: $97,760; Mid: $165,778; Senior: $227,400; Director: $250,000; VP: $250,000.
Klaviyo AI Hiring
Klaviyo has 3 open AI roles right now. They're hiring across AI Software Engineer, AI Product Manager. Based in Boston, MA, US. Compensation range: $222K - $324K.
Location Context
AI roles in Boston pay a median of $216,350 across 460 tracked positions. That's 8% above the national median.
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 4,133 open positions tracked in our dataset. By seniority: 106 entry-level, 1,901 mid-level, 1,663 senior, and 463 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (583 positions). The remaining 3,532 roles require on-site or hybrid attendance.
The market median for AI roles is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Safety ($274,200 median, 57 roles); AI Engineering Manager ($268,700 median, 42 roles); Research Engineer ($260,000 median, 442 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 4,133 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,865), Data Scientist (339), AI Software Engineer (313). 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 (106) are outnumbered by mid-level (1,901) and senior (1,663) 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 463 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (583 positions), with 3,532 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 $200,700. Top-quartile roles start at $254,000, and the 90th percentile reaches $307,500. 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 Safety roles lead at $274,200 median, while Prompt Engineer roles sit at $140,000. 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: Python (2,128 postings), Aws (1,324 postings), Azure (1,003 postings), Rag (916 postings), Gcp (817 postings), Pytorch (655 postings), Prompt Engineering (639 postings), Claude (571 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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