AI Product Engineer

Phoenix Ecommerce Technologies

United States

Hybrid

USD 120,000 - 150,000

Full time

14 days+

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Benefits offered by this job

Competitive compensation
Stock options
Benefits

Job summary

An innovative tech company is seeking a Senior AI Product Engineer to design and implement merchant-facing AI systems. You will manage the complete AI feature lifecycle, focusing on improving merchant outcomes. The ideal candidate has over 5 years of software engineering experience, strong backend skills, and a startup mindset. Join a team committed to innovation in AI-driven commerce. This hybrid position offers competitive compensation and benefits.

Qualifications

  • 5+ years of software engineering experience with production AI/LLM systems.
  • Experience designing multi-step reasoning systems.
  • Strong backend engineering skills (TypeScript/Node.js).

Responsibilities

  • Design and ship agent-driven features for merchants.
  • Build reliable LLM-backed services with controls.
  • Drive rapid experimentation to measure business impact.

Skills

Software engineering
AI/LLM systems
Backend engineering fundamentals
Prompt design
Agile methodologies

Job description

Location: Remote (US) / Hybrid optional in Weston, Florida
Why Join Phoenix?
  • Join a category-defining company with real traction ($10M+ ARR and growing).
  • Own a high-impact product domain in a breakout business.
  • Build and operate in an AI-native engineering culture.
  • Competitive compensation, stock options, and benefits.
  • Work alongside a driven, high-performing team committed to innovation and merchant success.
About Phoenix

Phoenix Technologies is the AI-native, operating system of performance commerce - empowering businesses to make the most money, with the least headache, on their own terms. We give direct response merchants an AI-native platform that unifies storefronts, checkout, payments, and OS — where agents handle the complexity, clients grow their business their way, and every business on Phoenix makes the platform smarter for the next.

We reached 8-figure ARR in our first two years — top 0.5% of all startups launched in 2024. We’re venture-backed, profitable on a per-merchant basis, and growing over 100% year over year.

Direct response represents a third of all e-commerce transactions, yet it’s been historically ignored by Silicon Valley. These are the product-led, move-fast brands — think Fashion Nova, Fabletics, Temu, and the thousands of entrepreneurs selling $50M+ annually who’ve been underserved by legacy platforms. We exist because they deserve better tools.

We’re at the inflection point where our AI investments are about to reshape how thousands of merchants operate daily. If you want to build at the frontier of AI and commerce — with real revenue, real merchants, and real scale — this is the place. Phoenix Technologies is the AI-native, operating system of performance commerce - empowering businesses to make the most money, with the least headache, on their own terms. We give direct response merchants an AI-native platform that unifies storefronts, checkout, payments, and OS — where agents handle the complexity, clients grow their business their way, and every business on Phoenix makes the platform smarter for the next.

Position Summary

We are hiring a senior AI Product Engineer to design and ship autonomous, merchant-facing AI systems. You will own the full lifecycle of AI-powered features - from concept to production impact - working closely with product, design, data engineering, and applied ML.

This role sits at the intersection of:

  • LLM-backed application systems
  • Distributed backend architecture
  • Product experimentation

Your focus is not research. It is shipping intelligent systems that measurably improve merchant outcomes (conversion, approvals, retention, efficiency).

Key Responsibilities

As an AI Product Engineer, you will:

  • Design and ship agent-driven features that execute multi-step workflows on behalf of merchants.
  • Build reliable LLM-backed services with strong latency, cost, and failure controls.
  • Translate model outputs and signals into real product behavior.
  • Implement evaluation, monitoring, and observability standards for AI-powered systems.
  • Drive rapid experimentation and A/B testing to measure business impact.
  • Contribute to architectural decisions that ensure scalability and maintainability.
  • Participate in production ownership and on-call rotation.

You will collaborate closely with:

  • Data Engineering, which owns event pipelines and feature infrastructure.
  • Applied ML, which owns predictive models and decision systems.

Your responsibility is turning intelligence into product experience.

Qualifications
  • 5+ years of software engineering experience, including shipping customer-facing production AI/LLM-powered systems.
  • Experience designing multi-step reasoning systems or tool-using agents.
  • Strong backend engineering fundamentals (TypeScript/Node.js or similar).
  • Deep understanding of prompt design, RAG patterns, and evaluation strategies.
  • Comfort operating production systems with real uptime and reliability constraints.
  • Hands-on experience using AI coding agents in your daily development workflow.
  • Familiarity with agile development methodologies and best practices (CI/CD, automated testing, code reviews).
  • Startup mindset: proven ability to thrive in high-growth, fast-paced environments.
Nice to have
  • Experience building AI systems that directly influence conversion, checkout performance, or payment outcomes in e-commerce environments.
  • Experience building agentic systems with tool use, memory, and planning capabilities.
  • Experience with LLMOps practices and tools.
  • Experience building MCP services.
What Success Looks Like at 12 Months
  • Multiple AI features driving measurable improvements in merchant KPIs.
  • Agent workflows operating reliably in production at scale.
  • Clear evaluation and monitoring pipelines for LLM-backed services.
  • Tight experimentation loops linking AI features to business outcomes.
  • A maintainable, scalable foundation for continued AI expansion.
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