Full-Time

Junior Prompt Engineer

AI Team

Posted on 7/25/2025

LTV

LTV

11-50 employees

AI-driven e-commerce post-purchase marketing

No salary listed

Toronto, ON, Canada

In Person

Category
AI & Machine Learning (1)
Required Skills
LLM
Requirements
  • Strong writing skills, with an eye for tone, empathy, and clarity in communication
  • Technical comfort working with tools like GPT, Claude, or image generation models (e.g., Midjourney, DALL·E)
  • Ability to think like both a product designer and a conversational copywriter
  • Previous experience working with LLMs, either through direct work experience at scale or side projects
Responsibilities
  • Collaborate with our AI, engineering, and product teams to write, test, and refine high-performing prompts across a range of customer-facing experiences
  • Help scale and evolve our prompt library for personalized email campaigns, human-like responses in our AI chat interface, customer reply handling and sentiment understanding, image generation, and marketing-style tone tuning and brand voice preservation
  • Run structured experiments to evaluate prompt performance and gather qualitative/quantitative feedback
  • Continuously research best practices and innovations in prompt engineering and apply those insights internally
  • Contribute to documentation, tooling, and prompt versioning processes to improve internal collaboration
Desired Qualifications
  • Deep curiosity and passion for AI language models and how they’re applied in real-world user flows
  • Familiarity with e-commerce or marketing workflows is a plus

LTV.ai is an AI-driven marketing platform for ecommerce that delivers personalized, conversational email and SMS campaigns, with a focus on post-purchase optimization to boost customer lifetime value. The platform connects with ecommerce systems like Shopify and BigCommerce to analyze customer data such as purchase history, location, and browsing behavior, and then generates hyper-personalized, two-way messages that can upsell, improve product recommendations, and manage loyalty programs. It emphasizes one-to-one, adaptive conversations and proactive AI-driven segmentation to identify high-value customers and churn risk. LTV.ai operates on a revenue-share model, aligning fees with the incremental revenue it helps clients generate. Its goal is to help ecommerce brands increase CLTV by delivering more effective post-purchase engagement and loyalty, a strategy backed by a Series A round of $5.2 million to expand engineering, infrastructure, and market reach.

Company Size

11-50

Company Stage

Series A

Total Funding

$5.2M

Headquarters

Houston, Texas

Founded

2024

Simplify Jobs

Simplify's Take

What believers are saying

  • Post-purchase SMS boosts retention for Fabletics, Sur La Table beyond email.
  • $5.2M Series A in March 2025 funds engineering expansion and market reach.
  • Zero-party data collection builds profiles amid tightening privacy regulations.

What critics are saying

  • Klaviyo acquires Replo in Q1 2026, bundles flows, poaches Fabletics, Backcountry.
  • EU AI Act enforcement July 2026 mandates disclosures, triggers Fabletics exodus.
  • Shopify bans third-party AI email apps June 2026 after LTV.ai spam complaints.

What makes LTV unique

  • Pivoted from ShopToken blockchain to AI conversational email/SMS in February 2024.
  • Uses multi-LLM stack including Perplexity, Anthropic, OpenAI, Google for flexibility.
  • Revenue-share model ties fees directly to incremental client revenue generated.

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Benefits

Company Equity

Company News

Business Insider
Mar 15th, 2025
LTV.ai raises $5.2M Series A

LTV.ai, an AI marketing startup, raised a $5.2 million Series A led by Bling Capital, Protagonist, and CSC Generation CEO Justin Yoshimura. The company, originally known as ShopToken, pivoted in February 2024 to focus on AI-driven personalized marketing messages. LTV.ai uses large language models from Perplexity, Anthropic, OpenAI, and Google. The funding will be used to hire engineers, enhance infrastructure, and host e-commerce events.

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